WO2013032933A2 - Methods, systems, and devices for intra-scan motion correction - Google Patents

Methods, systems, and devices for intra-scan motion correction Download PDF

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WO2013032933A2
WO2013032933A2 PCT/US2012/052349 US2012052349W WO2013032933A2 WO 2013032933 A2 WO2013032933 A2 WO 2013032933A2 US 2012052349 W US2012052349 W US 2012052349W WO 2013032933 A2 WO2013032933 A2 WO 2013032933A2
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gradient
computer
subject
magnetic resonance
correction
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PCT/US2012/052349
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French (fr)
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WO2013032933A3 (en
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Thomas Michael Ernst
Oliver Speck
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Kinecticor, Inc.
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Priority to EP12826869.5A priority Critical patent/EP2747641A4/en
Publication of WO2013032933A2 publication Critical patent/WO2013032933A2/en
Publication of WO2013032933A3 publication Critical patent/WO2013032933A3/en

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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00Arrangements or instruments for measuring magnetic variables
    • G01R33/20Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48NMR imaging systems
    • G01R33/54Signal processing systems, e.g. using pulse sequences ; Generation or control of pulse sequences; Operator console
    • G01R33/56Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
    • G01R33/565Correction of image distortions, e.g. due to magnetic field inhomogeneities
    • G01R33/56509Correction of image distortions, e.g. due to magnetic field inhomogeneities due to motion, displacement or flow, e.g. gradient moment nulling

Definitions

  • This invention relates generally to the field of biomedical imaging, and more specifically to a system for correcting defects in medical images that are caused by a subject's movement during an in vivo (in the living body) magnetic resonance scan.
  • Tomographic imaging techniques generate images of multiple slices of an object.
  • Some commonly used tomographic imaging techniques include magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) techniques, which are ideal for assessing the structure, physiology, chemistry and function of the living brain and other organs, in vivo and non-invasively.
  • MRI magnetic resonance imaging
  • MRS magnetic resonance spectroscopy
  • scans are of long duration, usually lasting several minutes.
  • To increase resolution (detail) of a tomographic scan more slices and more scanning steps must be used, which further increases the duration of a scan. Scans may also be of long duration in order to obtain sufficient signal-to-noise ratio.
  • Magnetic resonance techniques including tomographic techniques
  • MR magnetic resonance techniques
  • MRI Magnetic resonance techniques
  • an intra-scan motion correction system comprises: an electronic memory storage configured to store modules; and a computer processor configured to execute the modules comprising at least: a motion tracking module configured to receive pose data of a subject from one or more motion tracking systems during a magnetic resonance scan of the subject; and a correction gradient calculation module configured to calculate a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan.
  • an intra-scan motion correction system comprises: an electronic memory storage configured to store modules; and a computer processor configured to execute the modules comprising at least: a motion tracking module configured to receive pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and an error correction module configured to calculate a gradient moment based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the calculated gradient moment, and wherein the one or more errors in the gradient moment are corrected during reconstruction.
  • an intra-scan motion correction system comprises: an electronic memory storage configured to store modules; and a computer processor configured to execute the modules comprising at least: a motion tracking module configured to receive pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and an error correction module configured to calculate a phase based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the phase, and wherein the one or more errors in the phase are corrected during reconstruction.
  • a computer-implemented method of correcting for intra-scan motion during a magnetic resonance scan comprises: generating by a magnetic resonance scanner a magnetic field gradient and a radiofrequency signal for the magnetic resonance scan; tracking by a motion tracking system one or more pose parameters of a subject and transmitting pose data corresponding to the tracked one or more pose parameters at a given time to the magnetic resonance scanner; calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the transmitted pose data and a gradient sequence used for the magnetic resonance scan; applying by the magnetic resonance scanner the correction gradient to the subject prior to detecting signals emitted from the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan; and detecting by the magnetic resonance scanner the signals emitted from the subject for data acquisition, wherein the computer comprises a computer processor and an electronic storage medium.
  • a computer-implemented method of correcting for intra- scan motion during a magnetic resonance scan comprises: receiving by a motion tracking module pose data of a subject from one or more motion tracking systems during the magnetic resonance scan of the subject; and calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan, wherein the computer comprises a computer processor and an electronic storage medium.
  • a computer-implemented method of correcting for intra-scan motion during a magnetic resonance scan comprises: receiving by a motion tracking module pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and calculating by an error correction module a gradient moment based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the calculated gradient moment, and wherein the one or more errors in the gradient moment are corrected during reconstruction, wherein the computer comprises a computer processor and an electronic storage medium.
  • a computer-implemented method of correcting for intra-scan motion during a magnetic resonance scan comprises: receiving by a motion tracking module pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and calculating by an error correction module a phase based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the phase, and wherein the one or more errors in the phase are corrected during reconstruction, wherein the computer comprises a computer processor and an electronic storage medium.
  • a computer-readable, non-transitory storage medium has a computer program stored thereon for causing a suitably programmed computer system to process by one or more computer processors computer-program code by performing a method to correct for intra- scan motion during a magnetic resonance scan when the computer program is executed on the suitably programmed computer system, wherein the method comprises: generating by a magnetic resonance scanner a magnetic field gradient and a radiofrequency signal for the magnetic resonance scan; tracking by a motion tracking system one or more pose parameters of a subject and transmitting pose data corresponding to the tracked one or more pose parameters at a given time to the magnetic resonance scanner; calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the transmitted pose data and a gradient sequence used for the magnetic resonance scan; applying by the magnetic resonance scanner the correction gradient to the subject prior to detecting signals emitted from the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the
  • a computer-readable, non-transitory storage medium has a computer program stored thereon for causing a suitably programmed computer system to process by one or more computer processors computer-program code by performing a method to correct for intra-scan motion during a magnetic resonance scan when the computer program is executed on the suitably programmed computer system, wherein the method comprises: receiving by a motion tracking module pose data of a subject from one or more motion tracking systems during the magnetic resonance scan of the subject; and calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan, wherein the computer comprises a computer processor and an electronic storage medium.
  • a computer-readable, non-transitory storage medium has a computer program stored thereon for causing a suitably programmed computer system to process by one or more computer processors computer-program code by performing a method to correct for intra- scan motion during a magnetic resonance scan when the computer program is executed on the suitably programmed computer system, wherein the method comprises: receiving by a motion tracking module pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and calculating by an error correction module a gradient moment based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the calculated gradient moment, and wherein the one or more errors in the gradient moment are corrected during reconstruction, wherein the computer comprises a computer processor and an electronic storage medium.
  • a computer-readable, non-transitory storage medium has a computer program stored thereon for causing a suitably programmed computer system to process by one or more computer processors computer-program code by performing a method to correct for intra-scan motion during a magnetic resonance scan when the computer program is executed on the suitably programmed computer system, wherein the method comprises: receiving by a motion tracking module pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and calculating by an error correction module a phase based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the phase, and wherein the one or more errors in the phase are corrected during reconstruction, wherein the computer comprises a computer processor and an electronic storage medium.
  • FIG. 1A depicts an example illustrating the effects of motion of a subject during a magnetic resonance scan by a conventional MRI system.
  • FIG. IB depicts an example illustrating the effects of motion of a subject during a magnetic resonance scan by an adaptive MRI system.
  • FIG. 2 illustrates the effects of motion of a subject during a magnetic resonance scan in k-space.
  • FIG. 3 depicts an example of one embodiment of an intra-scan motion correction system coupled with a magnetic resonance scanner.
  • FIG. 4 is a time frame diagram illustrating an example of embodiments of one or more methods of intra-scan motion correction during a magnetic resonance scan.
  • FIG. 5 is a process flow diagram illustrating an example of an embodiment of an update geometry parameters block of an embodiment of a method of intra- scan motion correction during a magnetic resonance scan.
  • FIG. 6 is a process flow diagram illustrating an example of an embodiment of an update phase and/or read encoding gradient(s) block of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan.
  • FIG. 7 is a process flow diagram illustrating an example of an embodiment of an apply correction gradient block of an embodiment of a method of intra- scan motion correction during a magnetic resonance scan.
  • FIG. 7A is a process flow diagram illustrating an example of an embodiment of an apply correction phase block of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan.
  • FIG. 8 is a process flow diagram illustrating an example of an embodiment of an error correction block of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan.
  • FIG. 9 is a schematic diagram illustrating the effects of an example of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan.
  • FIG. 10 is a schematic diagram illustrating the effects of an example of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan.
  • FIG. 11 is a block diagram depicting one embodiment of a computer hardware system configured to run software for implementing one or more embodiments of the continuous intra-scan motion correction systems described herein.
  • the disclosure herein provides methods, systems, and devices for intra- scan motion correction during a magnetic resonance (MR) scan.
  • MR magnetic resonance
  • magnetic resonance techniques are broad interchangeable terms, and comprise without limitation magnetic resonance scan, magnetic resonance imaging, functional magnetic resonance imaging, diffusion magnetic resonance imaging, magnetic resonance tomographic techniques, magnetic resonance spectroscopy, other magnetic resonance-based techniques currently existing or to be developed in the future, and/or combinations thereof.
  • intra-scan motion correction is broad interchangeable terms, and comprise without limitation single, one or more, continuous, quasi-continuous, substantially continuous, nearly continuous, repeated corrections or the like for one or more errors due to motion of a subject during a magnetic resonance scan, wherein the corrections are applied during the magnetic resonance scan for any magnetic resonance techniques.
  • real time is broad interchangeable terms, and comprise without limitation real time, near real time, or substantially real time periods with minimal delay or lag, for example instantaneously, within 20-30 milliseconds, and/or within 2-3 seconds or longer.
  • MR scans typically have a long duration, so that motion of the subject is a substantial problem for acquiring accurate data. Consequently, subjects commonly are required to lie still to within one millimeter and one degree (better than the image resolution) over extended time periods.
  • These strict requirements cannot be met by many subjects in special populations, such as children and infants, patients with stroke, head trauma, dementia, very sick patients, subjects who are agitated or delirious perhaps due to anxiety or drug use, animals, or patients with movement disorders, resulting in data with motion artifacts.
  • anesthesia can be required.
  • anesthesia can cost about $900 and also has roughly 1/250,000 risk of death.
  • tomographic imaging techniques rely on detecting very small percentage changes in a particular type of signal, which makes these techniques even more susceptible to movement.
  • changes in the properties of blood in brain areas activated while subjects are performing tasks causes small signal changes (on the order of a few percent) that can be detected with MR.
  • small signal changes may easily be obscured by signal changes of similar or even greater size that occur during unintentional subject movements.
  • the basic problem is that it may take several minutes for a scan to be completed, but the patient or other object being scanned cannot remain sufficiently still for several minutes. Further, the space for a patient or other object being scanned (the "scanning volume") in an MR machine is very limited - there is very little space in an MR machine once a patient has been positioned inside for a scan.
  • the motion during the scan of a single dataset e.g. spectrum, 2D-slice, multiple slices or 3D-volume
  • the methods, systems, and devices for intra-scan motion correction can allow for magnetic resonance scan techniques, whether existing now or to be developed in the future, to be applied to many subjects, including those in special populations, such as children, infants, very sick patients, subjects who are agitated perhaps due to anxiety or drug use, or patients with movement disorders.
  • effects of movements of certain objects located within a subject such as internal organs of a subject, fetus, or the like, can also be corrected for in certain embodiments.
  • Further animals may also be subjected to a magnetic resonance scan by implementing one or more methods, systems, and devices for intra-scan motion correction as described herein.
  • inanimate objects that move may also be subjected to a magnetic resonance scan by implementing one or more methods, systems, and devices for intra-scan motion correction as described herein.
  • the methods, systems, and devices for intra-scan motion correction can substantially reduce the economic loss described above due to motion artifacts.
  • the methods, systems, and devices for intra-scan motion correction as described herein do not require that gradients track the rotation of the object of interest as other certain embodiments do or attempt to do. Rather, in some embodiments of the methods, systems, and devices for intra-scan motion correction as described herein, gradient rotations are specifically not updated within a single scan (between excitation and data acquisition). In other words, gradients remain stationary and do not track the motion of the subject to be scanned in some embodiments. The result is that at the end of the sequence, the Bloch equations governing magnetic resonance are not satisfied in some situations, which can introduce an error in the gradient moment. Some embodiments of the methods, systems, and devices for intra-scan motion correction as described herein can unexpectedly eliminate such error in the gradient moment by applying a single, brief, correction gradient of proper gradient moment prior to data acquisition.
  • subject movement can comprise rotations and/or translations.
  • Rotation matrices can be non-linear, due to the presence of sine and cosine terms. Therefore, if the Bloch equations are violated in some embodiments by not having gradients track subject movement, one might expect that the resulting phase errors become "non-linear" in space, and consequently cannot be corrected using linearly varying gradients.
  • theoretical analysis demonstrates that one can use linear gradients to correct the resulting. Accordingly, in some embodiments, the methods, systems, and devices for intra- scan motion correction as described herein can correct for motion artifacts not only due to translations, but also due to small and/or large rotations without having gradients track subject movement.
  • some embodiments of the methods, systems, and devices for intra-scan motion correction as described herein can be simple and not require a substantial amount of data processing. For example, in some embodiments, only one or more additional processes are required in addition to a general magnetic resonance scan process in order to correct for subject motion during the magnetic resonance scan. Accordingly, implementation of some embodiments of the methods, systems, and devices for intra-scan motion correction as described herein can be relatively easy and can be implemented in conjunction any and/or all existing magnetic resonance scan equipment and/or those to be developed in the future. Accordingly, the methods, systems, and devices for intra-scan motion correction as described herein can provide an unexpectedly simple yet accurate correction for any and/or all types of subject motion during a magnetic resonance scan.
  • specially designed scan sequences can be utilized to minimize the effects of constant motion during a single acquisition step without relevant organ shift during the entire acquisition.
  • a first order flow compensation can be utilized. While such embodiments are particularly useful for reducing artifacts or imaging errors due to flowing blood they are not particularly useful in correcting movements of entire organs, such as head movements.
  • improved sampling schemes for the magnetic resonance data can be used to reduce sensitivity to motion.
  • Such embodiments can reduce motion sensitivity of magnetic resonance scans under certain conditions. However, they are not particularly useful in correcting motions under other conditions or for very quick movements. Further such embodiments can require redundant measurements to encode additional information required for correction and thus reduce sampling efficiency. Such embodiments are also not generally applicable to all measurement techniques.
  • certain ultra-fast single shot imaging techniques can be utilized to account for movement by a subject during a magnetic resonance scan.
  • echo planar imaging, spiral imaging, or imaging using other fast trajectories can be utilized.
  • the entire organ of interest, such as a brain is scanned continuously every few seconds over the course of minutes, for instance, for functional magnetic resonance imaging, diffusion imaging, perfusion imaging, or other modalities.
  • functional magnetic resonance imaging, diffusion imaging, perfusion imaging, or other modalities By doing so, such embodiments make it possible to determine the pose defined as a position and rotation, for example of the head or other subject at each instant relative to the initial pose, using image -based registration and/or alignment of images.
  • the magnetic resonance scanner's image for that instant can be realigned to the initial image.
  • realignment of magnetic resonance imaging volumes comprising multiple slices can be used to correct for head motion and functional magnetic resonance imaging time series.
  • such embodiments are inherently slow because they use magnetic resonance imaging and may be unable to correct for motion in certain directions, such as orthogonal to the scan planes or towards or away from the planes in which the scans are being taken. Also, such embodiments correct movements only every few seconds (for each volume).
  • the various embodiments of reducing sensitivity of scans to subject motion typically do not account for variations in the subject's pose amongst the different k-space lines, even though motion sensitivity for each individual acquisition or a line in k-space is reduced. Further, the various embodiments of reducing sensitivity of scans to motions of a subject rather poorly tolerate fast or irregular movements within individual acquisition steps.
  • the pose of the subject of the scan and motion is tracked near-real time, during a scan.
  • the subject can be a head, brain, or other organ of interest or other object.
  • the pose information that is tracked can be used to compensate for the detected motion in data acquisitions for subsequent acquisition steps or slices or volumes within the same scan.
  • Such embodiments can be denoted "prospective motion correction" because the acquisition steps are adapted prospectively during the scan to compensate for the motion detected.
  • One important aspect of such embodiments of adapting imaging by prospective motion correction is the accuracy or resolution of the motion tracking system. Because of the high resolution generally required for biomedical imaging, the motion tracking system in such embodiments must also have a high resolution, because the motion tracking system's information will be used to align the various acquisition steps. Accordingly, if the motion tracking system's resolution is high enough, all of the acquisition steps can be accurately aligned or registered despite a subject's motion. Conversely, if the motion tracking system's resolution is not high enough, the acquisition steps will not be accurately aligned or registered.
  • magnetic resonance "navigator” signals can be utilized to estimate the pose of the subject and to dynamically correct for the subject's motion.
  • a magnetic resonance based navigator can also be utilized for adaptive motion correction in magnetic resonance imaging.
  • small radiofrequency coils can be utilized to track catheters during interventional magnetic resonance imaging.
  • magnetic resonance based adaptive magnetic resonance imaging techniques provide good or satisfactory results in many situations, they intrinsically interfere with the magnetic resonance acquisition process. Further, such embodiments can work only for a limited number of magnetic resonance sequences and can be limited to measuring the position or pose of a subject a few times per second at best.
  • external or non-magnetic resonance based techniques can be utilized to track subject motion rather than magnetic resonance based methods.
  • one or more optical methods can be utilized.
  • the pose information from the tracking system can be sent to the magnetic resonance scanner and be used by the scanner to compensate for the motion in subsequent acquisition steps.
  • stereovision can be utilized to track the motion of a subject, for example by using two or more cameras and multiple, at least two markers.
  • accurate tracking of the subject for example the head or brain or other organ, can be achieved using a single camera and a special marker in the magnetic resonance environment.
  • the special marker can be a self -encoded marker, a retrograde reflector or RGR or Moire Phase Tracking target.
  • Optical systems can provide accurate, non- contact sensing with a passive and non-magnetic target and can also provide fast pose updates on the order of 100 to 1,000 poses per second or even faster.
  • pose data from the tracking system are sent in near real time to a magnetic resonance scanner, which then nearly continuously updates scan parameters prior to each acquisition step or line in k-space. This way, the scan planes are locked relative to the moving object of interest. Images acquired with such embodiments of prospective motion correction can show substantially reduced motion artifacts compared to images acquired without motion correction.
  • pose data as received by the magnetic resonance scanner may be imperfect, for example due to inaccuracies or noise in the tracking system or due to lag times between the marker movement and arrival of tracking data on the scanner.
  • some of these inaccuracies or delays can be determined after the magnetic resonance scan has been acquired in certain embodiments as the entire tracking data are then available. More specifically, when prospective motion correction is applied, subject motion between the pose detection and magnetic resonance data acquisition can occur due to the time required to acquire and transfer marker images to the tracking computer, calculate pose information, perform magnetic resonance sequence updates, and the intrinsic timing of the sequence. Accordingly, differences between the assumed or estimated pose and the true pose during the acquisition step may cause residual motion artifacts.
  • inaccuracies in the tracking system can cause errors.
  • some of these effects of tracking errors on magnetic resonance signals can be corrected retrospectively within the data reconstruction by comparing the estimated or assumed pose from the tracking system and the true pose that is available after the acquisition step.
  • magnetic resonance acquisitions involve a sequence of events.
  • a common sequence involves excitation of the spin system using one or more radiofrequency pulses, possibly slice selective, spatial encoding using spatially variable switched magnetic fields (gradients), possible further manipulations of the spin system such as rephasing and complementary information encoding steps, and data acquisition.
  • excitation may be preceded by an extra module to prepare the spin system to achieve a certain contrast.
  • pose updates for prospective motion correction embodiments above have been applied immediately prior to excitation for each individual magnetic resonance acquisition or k-space line. Consequently, pose updates may be applied approximately ten times per second, even if the tracking system is capable of tracking at a higher rate, for example at 100 poses per second.
  • motion artifacts due to substantial intra-scan motion can be eliminated or attenuated by attempting to nearly continuously update magnetic field gradients and radiofrequency pulses during each acquisition. This way their orientation is perfectly aligned with the moving object of interest at any time.
  • such an embodiment can be implemented for diffusion-weighted magnetic resonance imaging, which involves very strong magnetic field gradients and is particularly sensitive to subject motion.
  • a single magnetic resonance acquisition step which typically involves a single sequence block of approximately 100 milliseconds for its application, can be broken down into multiple separate blocks, each lasting approximately two milliseconds. The direction of gradients for each of these two millisecond blocks can be updated using the most recent tracking data, resulting in a quasi-continuous pose update during the acquisition.
  • FIG. 1A illustrates the effects of a subject's motion during a magnetic resonance scan by a conventional magnetic resonance scanner.
  • a subject of a magnetic resonance imaging scan such as a head
  • the resulting slice or image from that scan which is stationary, inevitably becomes tilted relative to the subject as well.
  • Such movement by the subject during a scan can result in blurry and/or unclear images.
  • the acquired magnetic resonance scan may not be useful to a medical professional or the subject may be required to redo the entire magnetic resonance scan, resulting in an unnecessary burden in time and cost.
  • Figure IB illustrates the effects of a motion of a subject during a magnetic resonance scan by an intra- scan motion correction system. As illustrated in Figure IB, as the subject, or head in this example, is tilted or moved, the slice plane of the magnetic resonance scanner and/or phase and/or read orientations can also be tilted and/or adjusted to account for the motion of the subject.
  • a subject of a magnetic resonance imaging scan can be allowed to move with attenuated and/or without any such detrimental effects to the imaging results.
  • slow motions of a subject during a magnetic resonance scan can be defined as movements with speeds of about 1 mm/sec or 1 degrees/sec. Such slow motions can comprise slow drifts and can be nearly imperceptible.
  • Moderate motions of a subject during a magnetic resonance scan can be defined as movements with speeds of about 10 mm/sec or 10 degrees/sec. Such moderate motions are perceptible and can be common in children and sick or confused patients.
  • Fast motions of a subject during a magnetic resonance scan can be defined as movements with speeds of about 100 mm/sec or 100 degrees/sec or faster. Such fast motions can occur due to coughing or extreme agitation and can be limited in range and duration, for example 100 ms, due to confined space.
  • motion artifacts arising from slow and moderate motions can be accounted for.
  • even motion artifacts arising from fast motions can also be accounted for.
  • some effects of motion on moving spins can comprise unwanted phase shifts between excitation and signal readout, unwanted pose changes between phase-encoding steps (or lines in k-space), and uncorrected pose changes between successive slices or volumes.
  • Uncorrected pose changes between successive slices or volumes can occur in ultra-fast acquisitions that image the entire subject or brain every few seconds. Such volumes can be translated and rotated.
  • Unwanted pose changes between phase encoding steps can result in blurring; in other words, the object of interest can be imaged at variable poses.
  • unwanted phase shifts between excitation and signal readout can result in artifacts in the phase-encoding direction after image reconstruction.
  • the unwanted pose changes and uncorrected pose changes are purely geometric and thus can relatively easily be corrected. However, correcting phase shifts can be more complicated.
  • the magnetic resonance scanner detects the sum of magnetization of the individual spins in a given volume. The sum of signals from all individual spins is detected.
  • phases of individual spins need to be coherent or aligned. Loss of phase coherence of spins can cause signal attenuation or loss.
  • gradients have to be balanced throughout a pulse sequence, because gradients affect a spin's frequency and phase dependent on the spin's spatial position.
  • the phase of the signals detected has to be aligned across acquisition steps or lines in k-space. However, motion interferes with this process by inducing unintended phase shifts.
  • the motion of the object of interest can first be characterized mathematically.
  • the object of interest can be assumed for example to be a rigid body.
  • the pose of the object can be characterized by six time dependent parameters, three translations and three rotations.
  • a pose of an object can be considered to comprise six degrees of freedom.
  • orientation of an object can comprise two or more degrees of freedom, three or more degrees of freedom, four or more degrees of freedom, or five or more degrees of freedom.
  • the 3 translations can form a translation vector X( t) and the 3 rotations can form a rotation matrix R(t), where t represents time.
  • a magnetic resonance sequence generally involves a series of radiofrequency pulses, switched magnetic field gradients, and one or more acquisition events.
  • Motion within this sequence (“intra-scan motion") alters both the zero-order phase (due to translations) and effective gradient moment M (due to rotations) in the object coordinate system.
  • Translations X( t) will cause a change in the overall phase ⁇ of the object at the time T of data acquisition, and rotations R(t) will cause a change in the gradient moment M of the object at the time T of data acquisition. It can be shown that the effects of translations and rotations are as follows:
  • phase and gradient moment effects caused by intra- scan motion arise from the interaction between the moving object and switched magnetic field gradients.
  • most embodiments of non-continuous motion correction methods consider only geometric effects of motion, such as ensuring that scan planes are aligned correctly during scans (see, for example, FIGURE IB), with the exception of the quasi-continuous embodiment described above.
  • the geometric effects and phase/gradient moment effects are conceptually entirely different. For instance, phase effects may occur even if all geometric effects are corrected, and vice versa. Accordingly, in order to accurately correct for movement and/or motion of a subject during a magnetic resonance scan, both geometric effects and phase/gradient moment effects must be accounted for.
  • Figure 2 illustrates the phase/gradient movement effects in generating a magnetic resonance image via k-space when the subject moves in orientation and/or pose.
  • a subject of a magnetic resonance scan remains completely still and does not move, the data acquired from such scan is generally placed in the correct position of k-space which is denoted by the intersection between the center vertical line and one or more solid horizontal lines as depicted in Figure 2.
  • the data acquired cannot be placed in the correct k-space either vertically and/or horizontally.
  • Vertical displacement, or placing an acquired data off of a horizontal parallel line denotes an error in the phase encoding.
  • Horizontal displacement, or placing an acquired data off of the center vertical line denotes an error in the read encoding or frequency encoding.
  • the x axis in k-space is encoded by a read gradient
  • the y axis in k-space is encoded by a phase gradient.
  • the phase encoding gradient, or the read encoding gradient, or both the phase encoding gradient and the read encoding gradient must be updated according to the detected motion of the subject in order to account for substantially all motion effects by the subject during the scan.
  • rotations in space generally correspond to rotations in k-space.
  • rotations of the subject may be corrected by adjusting phase encoding gradients and/or frequency encoding gradients so that they match the rotation of the subject to be scanned.
  • translations of the subject can essentially be approximated by phase shifts that vary linearly in k-space and corrected for intra-scan or during image reconstruction.
  • embodiments of the intra-scan motion correction systems, methods, and devices described herein comprise one or more techniques of targeting these effects. Also, embodiments of the intra-scan motion correction systems, devices, and methods described herein generally use less data processing capabilities compared to the quasi-continuous embodiment described above and can be utilized with the majority of currently available magnetic resonance scanners. Additionally, prospective update errors due to the inherent lag time, noise, or the like in the quasi-continuous correction embodiment described above can be eliminated in embodiments of the intra-scan motion correction system, methods, and devices described herein.
  • FIG. 3 illustrates an embodiment of a system for intra-scan motion correction.
  • An intra-scan motion correction system can be configured to be used in conjunction with one or more magnetic resonance scanners.
  • a magnetic resonance scanner can comprise an intra-scan motion correction system.
  • a magnetic resonance scanner and an intra-scan motion correction system are physically separate.
  • one or more parts or modules of a magnetic resonance scanner and an intra-scan motion correction system are shared and/or accessible by the other.
  • an embodiment of an intra-scan motion correction system can generally comprise a main computing system 300, a user interface 302, and a display for outputting constructed images 334.
  • the user interface 302 can allow a medical professional and/or other user to control the intra-scan motion correction system and/or magnetic resonance system, such as turning the system on or off and/or controlling one or more parameters of the system.
  • a user can instruct the main computing system 300 to turn a magnetic field gradient 304 on or off by transmitting the instruction from the main computing system 300 to a magnetic field gradient generator 304.
  • a user can use the user interface 302 to instruct the main computing system 300 to turn a radiofrequency signal generator 306 on or off and also control the radiofrequency signal generator 306 to emit a radiofrequency signal of a certain type.
  • the motion tracking system 310 can track substantially any and all motion of the subject 308 during a magnetic resonance imaging scan.
  • the motion tracking system 310 can comprise any of the motion tracking systems that are currently known or to be developed in the future.
  • the motion tracking system 310 can be an optical or stereo vision system (in-bore or out-bore), optical system with multiple cameras (in-bore or out-bore), laser-based tracking system with or without a reflector (in-bore or out-bore), radiofrequency pickup coils-based system (in-bore), magnetic field gradient monitoring system (in-bore), wire loop recordings-based system (for example, using EEG equipment), self-encoded marker-based system, single camera-based system (in-bore or out-bore), mechanical detection system, magnetic field gradient monitoring-based system, ultrasound- based system, or the like.
  • the tracking data can be transmitted from the motion tracking system 310 to the main computing system 300.
  • the motion tracking system 310 is configured to track and/or send data related to the motion of the subject 308 in real time.
  • the motion tracking data that is collected by the motion tracking system 310 is transmitted to the main computing system 300 over a computer network periodically in packets of data. In other embodiments the motion tracking data collected by the motion tracking system 310 is transmitted over a computer network to the main computing system 300 at once in a relatively large data packet.
  • the magnetic field gradient and/or radiofrequency signals that are generated by the magnetic field gradient generator 304 and radiofrequency signal generator 306 respectively can affect the magnetization of one or more nuclei of the subject 308. By manipulating the magnetic field gradient and radiofrequency signal, such generated magnetization can be further manipulated in the subject 308, resulting in a signal emission from the subject 308.
  • the emitted signal can be detected by one or more magnetic resonance detector devices and/or receivers 312. Such detected data by the magnetic resonance detector device and/or receiver can be transmitted over a computer network or another connection to the main computing system 300.
  • the data transmitted from the motion tracking system 310 to the main computing system 300 can be further processed by the motion tracking module 314.
  • the motion tracking module 314 can be configured to generate a motion trajectory of the subject 308. Any such motion data that is transmitted from the motion tracking system 310 and/or motion data that is further processed by the motion tracking module 314 can be stored in a database 332 of the main computing system 300.
  • a geometry update module 316 can be configured to update and/or adjust one or more geometric parameters accordingly in order to compensate for the subject's motion. Any or all geometric parameter updates by the geometry update module 316 can further be stored in the database 332 of the main computing system 300.
  • a phase encoding update module 318 can be configured to update one or more phase encoding gradients.
  • the phase encoding gradient updates that are processed by the phase encoding update module 318 can further be stored in the database 332 of the main computing system 300.
  • a read encoding gradient update module 320 can be configured to update one or more read encoding gradients based on the motion of the subject 308 as detected by the motion tracking system 310.
  • the read encoding gradient updates that are processed by the read encoding update module 320 can further be stored in the database 332 of the main computing system 300.
  • the main computing system 300 can further comprise a magnetic resonance sequence module 324.
  • the magnetic resonance sequence module 324 can be configured to process a particular magnetic resonance sequence or a series thereof for one or more magnetic resonance scans.
  • the processed magnetic resonance sequence can be generated by the magnetic field gradient generator and/or radiofrequency signal generator 306 and applied to a subject 308.
  • the magnetic resonance sequence module 324 can further be configured to track or log one or more magnetic resonance sequences, which can then be stored in the database 332 of the main computing system 300.
  • a correction gradient calculation module 326 of the main computing system 300 can be configured to calculate a first gradient moment during one or more magnetic resonance scans. More specifically, in certain embodiments, the correction gradient calculation module 326 is configured to calculate the (first) gradient moment according to Equation 1 and using the tracked pose and/or orientation data and a gradient signal and/or sequence used during one or more scans.
  • the (first) gradient moment is the time integral of the gradient waveform. In other words, the (first) gradient moment is the area beneath the gradient waveform when plotted against time.
  • the gradient waveform can be triangular, trapezoidal, sinusoidal or the like in shape.
  • the gradient waveform may be a superposition of a non-corrected gradient waveform with a triangular, trapezoidal, sinusoidal, waveform or the like in shape.
  • the only property of the gradient waveform that is required in a method for intra-scan motion correction is the first gradient moment according to Equation 1.
  • a correction gradient or a "blip" gradient can be applied to the subject 308 in order to counteract and/or reverse the effects of the altered first gradient moment.
  • the correction gradient calculation module 326 is further configured to determine an appropriate correction gradient moment to be applied to the subject 308.
  • the appropriate correction gradient moment can be equal to the first gradient moment in absolute value but with an opposite sign from the first gradient moment according to Equation 1. In other words, by applying a correction gradient with a moment of -M, motion artifacts caused by a gradient moment of M can be accounted for and the signal phase can be corrected.
  • a correction gradient of a moment as determined by the correction gradient calculation module 326 can be applied to a subject 308 by a magnetic field gradient generator 304. Further, in some embodiments, the (first) gradient moment and/or correction gradient moment that is calculated can be stored in a database 332 of the main computing system 300.
  • a phase correction module 328 can be configured to correct errors in one or more constant phases due to subject motion (according to equation 2) prior to data acquisition, during data acquisition, and/or during the reconstruction process of the image.
  • the phase correction module 328 is configured to correct errors based on the tracked pose data and/or Equation 2.
  • the phase corrections that are processed by the phase correction module 328 can further be stored in the database 332 of the main computing system 300.
  • the main computing system 300 can also comprise an error correction module 330.
  • the error correction module 330 can be configured to identify and correct any residual errors that remain after data acquisition.
  • the error correction module 330 can be configured to identify and/or correct errors in orientation, pose, and/or phase.
  • the error correction module 330 can be configured to correct one or more residual errors in one or more geometry parameters and/or signal phase and/or first gradient moment that are present after applying or without applying one or more geometry updates, phase encoding updates, read encoding gradient updates, and/or application of an additional magnetic moment correction gradient.
  • the error correction module 330 can be configured to retrospectively correct errors in one or more geometry parameters, gradient moment, and/or phase.
  • the error correction module 330 can be configured to correct for one or more errors due to lag time in obtaining and processing orientation and/or pose data, noise in data, or the like. For example, due to such lag time and/or noise, errors may exist in one or more geometry updates, phase encoding gradient updates, read encoding gradient updates, and/or calculation of a correction gradient, because all such calculations are based in part on the tracked pose and/or orientation data. Because the true pose and/or orientation data are available after data acquisition or a scan is complete, such discrepancies due to lag time or noise can be resolved. Further, any such residual errors that are corrected by the correction module 330 can further be stored in a database 332 of the main computing system 300.
  • the main computing system 300 can further comprise an image construction module 322.
  • the image construction module 322 can be configured to construct and/or reconstruct an image based on the one or more signals emitted from the subject 308.
  • the image construction module 322 can further be configured to construct and/or reconstruct an image based in part on data that is processed by the magnetic resonance imaging sequence module 324, the geometry update module 316, phase encoding update module 318, read encoding gradient update module 320, correction gradient calculation module 326, and/or the correction module 330.
  • An image that is constructed and/or reconstructed by the image construction module 322 can further be transmitted over a computer network or other connection to one or more displays for outputting a constructed image 334.
  • a user and/or medical professional can view the constructed image via the display for outputting the constructed image 334.
  • Figure 4 is a time frame diagram that illustrates the time frame of one or more methods for an intra-scan motion correction.
  • a method for an intra-scan motion correction can comprise one or more blocks, including but not limited to an update geometry parameters block, an update phase and/or read encoding gradient(s) block, an apply correction gradient block, and/or an error correction block or any sub-blocks thereof.
  • a method for intra-scan motion correction can comprise a phase correction block.
  • a method for intra-scan motion correction can comprise any selective combination of these blocks and/or more specific blocks thereof.
  • the update geometry parameters block, update phase and/or read encoding gradient(s) block, apply correction gradient block, and apply phase correction block can be applied on a magnetic resonance scanner in near real-time.
  • the error correction block can be applied after data acquisition during image reconstruction.
  • other implementations are possible as well.
  • an update geometry parameters block can comprise updating a prospective slice and/or geometry 402.
  • the prospective slice and/or geometry update can occur immediately before one or more radiofrequency pulses.
  • a prospective slice and/or geometry update can occur prior to and/or immediately prior to excitation via an initial radiofrequency pulse.
  • the prospective slice and/or geometry update can also occur prior to and/or immediately prior to an optional initial magnetic gradient field.
  • a prospective slice and/or geometry update can occur prior to and/or immediately prior to any additional radiofrequency pulses and/or optional magnetic gradient fields.
  • an update phase and/or read encoding gradients block can comprise prospectively updating the orientation or pose of a phase encoding gradient and/or a frequency (read) encoding gradient.
  • the prospective phase encoding gradient update can occur at any time between excitation and data acquisition 410.
  • a prospective phase encoding gradient update 404 can occur immediately after excitation and/or an optional magnetic gradient field.
  • a prospective phase encoding gradient update 404 can occur at a time after excitation and/or optional magnetic gradient field.
  • a prospective phase encoding gradient update 404 can occur in connection with an additional radiofrequency pulse and/or optional magnetic gradient field.
  • a prospective phase encoding gradient 404 can occur concurrently with and/or in conjunction with a data acquisition process 410.
  • a prospective frequency encoding gradient update 406 can begin prior to and/or immediately prior to a data acquisition process 410. In certain embodiments, a prospective frequency encoding gradient update 406 can occur concurrently with and in conjunction with a data acquisition process 410. In certain embodiments, a prospective frequency encoding gradient update 406 can end immediately prior to the end of a data acquisition process 410.
  • An apply correction gradient block can comprise applying a brief additional gradient 408 to the subject to correct for a first gradient moment as discussed above.
  • the correction gradient 408 can be applied after excitation and/or optional magnetic gradient fields and any additional radiofrequency pulses and/or optional magnetic gradient fields.
  • the correction gradient 408 can be applied to the subject immediately prior to data acquisition 410.
  • the correction gradient 408 can be applied to the subject concurrently with any other magnetic field gradient.
  • an apply phase correction block can comprise setting the phase of the MR detector or receiver, or the phase of the data acquisition 410 device to correct for zero-order phase errors 409 as determined by Equation 2.
  • the phase correction block can be applied to the subject immediately prior to or concurrent with data acquisition 410.
  • an error correction block can comprise correcting any residual error 412 after data acquisition.
  • residual errors in one or more geometry parameters, phase, and/or gradient moments are corrected in the error correction block. Such errors can be present after applying or without applying one or more geometry updates, phase encoding updates, read encoding gradient updates, phase corrections and/or application of an additional correction gradient.
  • residual errors can remain after processing the magnetic resonance data, with or without the update geometry parameters block, update phase and/or read encoding gradients block, and/or apply correction gradient block.
  • the error correction 412 can occur after and/or immediately after data acquisition 410.
  • the system is configured to construct and/or reconstruct an image of the subject 414.
  • the system can be configured to reconstruct the image based on the magnetic resonance data as inputted into k-space.
  • the system is configured to reconstruct an image further based on prospectively updated slices, phase encoding gradient updates, frequency encoding gradient updates, application of a correction gradient, and/or error correction.
  • one or more geometry parameters are updated prospectively.
  • one or more geometry parameters can be updated after excitation but before data acquisition.
  • prospectively updating one or more geometric parameters rather than after data acquisition, data processing time can be saved and a more isotropic, rectangular coverage of k-space can be obtained.
  • certain areas in k-space can be denser than others, possibly resulting in image artifacts and/or more complex reconstruction.
  • certain signals may be attenuated or lost, and cannot be recovered during image reconstruction.
  • Figure 5 illustrates a process flow of an example of embodiments of one or more methods of intra-scan motion correction during a magnetic resonance scan.
  • the update geometry parameters block can be applied alone or in conjunction with one or more of an update phase and/or read encoding gradient(s) block, apply correction gradient block, apply correction phase block, and/or error correction block or sub-blocks thereof.
  • the orientation and/or pose of a subject is tracked via one or more motion detectors at block 502. Based on the tracked orientation and/or pose of the subject the system can be configured to prospectively update one or more geometric parameters and/or slice planes at block 504.
  • the one or more geometric parameters can comprise one or more parameters discussed above, including but not limited to translation and rotation.
  • the prospective update of geometric parameters and/or slice planes 504 can occur prior to and/or immediately prior to excitation of the spin system by applying an initial radiofrequency pulse at block 506. Further, the excitation can occur in conjunction with an optional magnetic field gradient at block 506.
  • Subsequent prospective updates of geometric parameters and/or slice planes can occur at block 508. As discussed, any of one or more, if any, subsequent prospective updates of geometric parameters and/or slice planes 508 can occur prior to and/or immediately prior to applying additional radiofrequency pulses at block 510.
  • the radiofrequency pulses can be slice-selective refocusing, and/or slice-selective saturation and/or inversion pulses among others.
  • the additional radiofrequency pulses can also be applied in conjunction with, before, and/or after applying an optional magnetic field gradient at block 510.
  • the system can be configured to conduct data acquisition at block 512 based on the scanned magnetic resonance data.
  • phase and/or read encoding gradients are prospectively updated.
  • data processing time can be saved and a more isotropic, rectangular grid in k-space can be obtained. In other words, a more homogeneous coverage in density in k-space is possible.
  • phase and/or read encoding gradients are updated only retrospectively after data acquisition, certain areas in k- space can be denser than others, possibly resulting in more complex reconstruction and/or in image artifacts. Further, if the phase and/or read encoding gradients are updated only retrospectively after data acquisition, certain signals may be encoded incorrectly, and cannot be recovered during image reconstruction.
  • Figure 6 illustrates an example of an embodiment of an update phase and/or read encoding gradient(s) block of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan.
  • the update phase and/or read encoding gradient(s) block can be applied alone or in conjunction with one or more of an update geometry parameters block, apply correction gradient block, apply correction phase block , and/or error correction block or sub-blocks thereof.
  • one or more motion detectors are configured to track the orientation and/or pose of the subject during a magnetic resonance scan.
  • the system can further be configured to apply excitation of the spin system at block 604 by applying a radiofrequency pulse. In certain embodiments excitation of the spin system can occur in conjunction with, before, and/or after applying an optional magnetic field gradient at block 604.
  • the orientation of a phase encoding gradient can be updated at any time after excitation and/or in conjunction with data acquisition 614.
  • Prospectively updating the orientation of read encoding gradient and/or phase encoding gradient can occur at one or more of the blocks depicted in Figure 6.
  • a phase encoding gradient can be prospectively updated at block 606 after excitation of the spin system at block 604.
  • a prospective update of the phase encoding gradient need not occur at this time.
  • a prospective update of the phase encoding gradient can occur at block 610 after applying one or more additional radiofrequency pulses at block 608.
  • any additional radiofrequency pulses can be applied at block 608 in conjunction with, before, and/or after applying an optional magnetic field gradient.
  • a prospective update of the orientation of read encoding gradient can occur at block 612 immediately prior to data acquisition at block 614.
  • the read encoding gradient can be updated at block 616 in conjunction with data acquisition at block 614.
  • the read encoding gradient can be updated immediately prior to data acquisition 614 at block 612 and repeatedly in conjunction with data acquisition 614 at block 616.
  • the phase encoding gradient can also be updated in conjunction with data acquisition 614 at block 618.
  • the first gradient moment over the scan should ideally equal zero for a balanced magnetic resonance sequence. However, if a subject of a magnetic resonance scan moves even slightly, the first gradient moment after completion of the scan does not equal zero.
  • the transverse magnetization generated by the excitation pulse is affected by motion that occurs in the presence of gradients. Such motion affects the phase of the magnetization and thus the first order gradient moment depending on the direction and velocity of motion, and the direction and sequence of the gradients applied.
  • Figure 7 illustrates an example of an embodiment of an apply correction gradient block of an embodiment of a method of intra- scan motion correction during a magnetic resonance scan.
  • the apply correction gradient block can be applied alone or in conjunction with one or more of an update geometry parameters block, update phase and/or read encoding gradient(s) block, apply correction phase block, and/or error correction block or sub-blocks thereof.
  • the system can be configured to track the orientation and/or pose of a subject during the scan via one or more motion detectors at block 702.
  • the spin system is excited by applying an initial radiofrequency pulse at block 704.
  • the excitation can be applied in conjunction with one or more optional magnetic field gradients at block 704.
  • the system can be configured to apply additional magnetic field gradients.
  • Such magnetic field gradients can comprise, for example, diffusion weighting gradients, flow encoding gradients, elasticity encoding gradients, gradients to eliminate unwanted spin coherences called spoiler or crusher gradients, gradients to prewind or rewind gradient moments, and/or other gradients.
  • one or more additional radiofrequency pulses can be applied to the subject at block 706. These one or more additional radiofrequency pulses can also be applied in conjunction with, before, and/or after applying one or more optional magnetic field gradients at block 706. Apply Phase Correction Block
  • phase of the signal is altered.
  • the transverse magnetization generated by the excitation pulse is affected by motion that occurs in the presence of gradients. Such motion affects the phase of the magnetization depending on the direction and velocity of motion, and the direction and sequence of the gradients applied.
  • Motion affects both the phase of the signals acquired, as well as the gradient moment / position of "lines" in k-space. If the movement is known or predicted, then the phase effect can be calculated as per Equation 2. Phase alterations as per equation 2 may be compensated for by acquiring data at the correct reference-phase.
  • a method of intra-scan motion correction comprises an apply correction phase block.
  • Figure 7A illustrates an example of an embodiment of an apply correction phase block of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan.
  • the apply phase gradient block can be applied alone or in conjunction with one or more of an update geometry parameters block, update phase and/or read encoding gradient(s) block, apply gradient correction block, and/or error correction block or sub-blocks thereof.
  • the apply correction phase block can comprise calculating the correction phase at block 720. More specifically, Equation 2 and the tracked pose can be utilized to calculate the correction phase. The calculated correction phase can be applied to compensate for any or all phase effects at block 722. Further, the system can be configured to conduct data acquisition at block 724 after applying the correction gradient block in some embodiments.
  • phase/gradient error and orientation error can be present in the data acquired.
  • phase/gradient error and orientation error can be present in the data acquired.
  • the prospective update blocks are based on packets of orientation and/or pose data that are transmitted periodically from one or motion detectors to the computing system.
  • an error correction block is applied to retrospectively correct for any remaining error.
  • Figure 8 is a process flow diagram illustrating an error correction block.
  • the error correction block can be applied alone or in conjunction with one or more of an update geometry parameters block, update phase and/or read encoding gradient(s) block, apply correction phase block, and/or apply correction gradient block or sub-blocks thereof.
  • a system can be configured to track the orientation and/or pose of a subject during a magnetic resonance imaging scan via one or more motion detectors at block 802.
  • the spin system can be excited by applying an initial radiofrequency pulse at block 804.
  • the excitation in certain embodiments, can be applied in conjunction with applying an optional magnetic field gradient at block 804.
  • the system can be configured to apply one or more additional radiofrequency pulses at block 806.
  • the one or more additional radiofrequency pulses can also be applied in conjunction with, before, and/or after one or more magnetic field gradients.
  • the magnetic resonance scan data can be collected at block 808 by the system in some embodiments.
  • Any residual errors that are present after data acquisition 808 can be determined by the system and/or corrected during an error correction block. For example, any residual errors in one or more geometry parameters and/or phase or gradient moment that are present after applying or without applying one or more geometry updates, phase encoding updates, read encoding gradient updates, and/or application of an additional correction gradient can be corrected.
  • the system can be configured to determine discrepancies between predicted motion, from the orientation and/or pose data that was collected and transmitted periodically to the system at block 802, and the actual motion data at block 810.
  • the actual motion data in certain embodiments, can only be determined after the data acquisition process is complete.
  • errors in the predicted motion from the orientation and/or pose data that is periodically detected and sent to the system at block 802 can comprise one or more errors due to the inherent lag time and/or noise. Because of such potential errors in the predicted motion data, there can also be some residual errors in orientation and/or pose or phase/gradient even after applying one or more of an update geometry parameters block, update phase and/or read encoding gradient(s) block, apply correction gradient block, apply correction phase block, and/or sub-blocks thereof. Such residual errors can be corrected during the error correction block based on the determined discrepancies between the predicted motion and actual motion.
  • small errors in the orientation of phase and read-encoding gradients can also be corrected during reconstruction, for instance, by interpolating the originally acquired raw data to a rectilinear raw data grid prior to Fourier transformation.
  • the system can be configured to reconstruct an image based on the magnetic resonance scan, orientation and/or pose update, phase encoding gradient update, read gradient update, application of correction gradient, apply correction phase block, and/or any errors corrected during the error correction block at block 814.
  • Figure 9 is a schematic diagram illustrating the effects of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan.
  • the illustrated embodiment in Figure 9 comprises prospectively updating one or more geometry parameters, prospectively updating phase and/or read gradient(s), and applying a correction gradient.
  • one or more slice updates or geometric updates are applied prior to and/or immediately prior to one or more radiofrequency pulses, including but not limited to excitation of the spin system.
  • RF1 through RF3 correspond to one or more radiofrequency pulses.
  • a slice update can occur immediately prior to application of radiofrequency pulse RF1.
  • another slice update can occur immediately prior to another radiofrequency pulse RF2.
  • another slice update can occur immediately prior to applying another radiofrequency pulse RF3.
  • PI through P7 correspond to individual periodic packets of orientation and/or pose data that is detected by one or more motion detectors and transmitted to the magnetic resonance system in some embodiments.
  • one or more slice updates can be applied by the system using the orientation and/or pose data packet that was transmitted to the system immediately prior to one or more slice updates and/or geometric updates. For example, a first slice update can be applied based on data packet PI. Further, another slice update can be applied based on the orientation and/or pose data packet P2. Additionally, another slice update can occur using the orientation and/or pose data packet P6.
  • the depicted embodiment prospectively updates geometric parameters within a single magnetic resonance scanning step to obtain clearer images.
  • the second horizontal line denoted SL corresponds to slice gradients and updates.
  • the one or more slice updates are applied immediately prior to one or more radiofrequency pulses using an orientation and/or pose data packet that was received immediately prior to the slice update.
  • the third horizontal line denoted PH corresponds to phase encoding direction.
  • the phase encoding gradient in some embodiments is updated immediately prior to data acquisition, which is labeled AQ.
  • the data acquisition can last for anywhere from about one milliseconds to about 100 milliseconds or longer.
  • the fourth horizontal line denoted RO corresponds to the readout direction.
  • the read encoding update is applied immediately prior to or concurrently with data acquisition.
  • read encoding update is not required. Rather, only phase encoding update and/or geometry update is applied.
  • Gl through G4 in the PH horizontal line correspond to additional magnetic field gradients used to encode additional information, such as microscopic diffusion of molecules, or to eliminate unwanted signals, or for other purposes.
  • additional magnetic field gradients used to encode additional information, such as microscopic diffusion of molecules, or to eliminate unwanted signals, or for other purposes.
  • the system is configured to apply an additional brief gradient or a correction gradient to reverse the effects of the total gradient moment.
  • the correction gradient is simply the inverse of the gradient moment build-up.
  • a "blip" or a correction gradient moment is calculated prior to or immediately prior to data acquisition.
  • orientation and/or pose data packets from the entire scan duration can be used.
  • P1-P7 can be used in conjunction with the gradient sequence to calculate the gradient moment build-up.
  • lag time and/or noise may be present in the orientation and/or pose data packets.
  • it requires time for data packet P5 to be transmitted from one or more motion detectors to the computer system and to be processed.
  • lag time and/or noise in orientation and/or pose data leads to possible errors in the prospective updates to one or more geometry parameters, phase/gradient, and/or calculation of a correction gradient.
  • the one or more motion detectors can be configured to continue to collect orientation and/or pose data, for example P8 and/or P9. With such continued data, the lag time can be accounted for. For example, each data packet can be shifted in time by a certain amount in order to account for the lag time. By shifting the time of orientation and/or pose data, the system can obtain true orientation and/or pose data and determine and/or correct any errors remaining after data acquisition.
  • FIG 10 is another schematic diagram illustrating the effects of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan.
  • the first horizontal line RF illustrates the radiofrequency sequences.
  • G SL , G PE , and G RO represent slice gradient, phase encoding gradient, and readout gradient respectively.
  • the echo time (TE) corresponds to the time between the center or excitation and the center of data acquisition. Similar to Figure 9, a slice update is conducted by the system immediately prior to excitation. Further, a phase encoding gradient update is conducted by the system between excitation and data acquisition. Additionally, a correction gradient is applied by the system to the subject before data acquisition. The correction gradient in Figure 10 is illustrated by the pulses located within the oval.
  • a read encoding gradient update can be conducted by the system in conjunction with data acquisition. For example, a read encoding gradient update process can begin immediately prior to data acquisition and continue to be conducted throughout the data acquisition process.
  • Repetition time refers to the time between the excitation of a first scan and a second scan.
  • non-intrascan motion correction systems update scan parameters only once prior to each "excitation” radiofrequency (RF) pulse, which is typically every 100ms or less frequently. Further, some of such embodiments only correct slice locations. Since the subject position and orientation is assumed to be static between a given "excitation” and “readout", such a scheme can work well for relatively slow movements, on the order of a few millimeters / second. However, more rapid movements require dynamic updates of sequence parameters (for instance every few milliseconds) between excitation and acquisition, i.e. within each line of k-space. Of note, some tracking techniques, such as optical techniques, can allow very rapid and accurate tracking, from 100 to up to 1000 times per second.
  • RF radiofrequency
  • the concepts described herein can generally be applied to any imaging or spectroscopy sequence and therefore can constitute a universal method to compensate the effects of subject motion in any MR scan.
  • data may not be acquired in k-space (i.e. without use of readout gradients); however, the methods disclosed can be used to eliminate phase errors and / or imbalances in gradient moments due to motion, which otherwise result in signal reduction and spectral distortions due to non coherent averaging of signals.
  • some imaging techniques use non-rectangular sampling in k-space, but the methods described can easily be adapted to such sampling schemes.
  • the computer clients and/or servers described above take the form of a computing system 1100 illustrated in Figure 11, which is a block diagram of one embodiment of a computing system that is in communication with one or more computing systems 1110 and/or one or more data sources 1120 via one or more networks 1116.
  • the computing system 1100 may be used to implement one or more of the systems and methods described herein.
  • the computing system 1100 may be configured to apply one or more of the intra-scan motion correction techniques described herein. While Figure 11 illustrates one embodiment of a computing system 1100, it is recognized that the functionality provided for in the components and modules of computing system 1100 may be combined into fewer components and modules or further separated into additional components and modules.
  • the system 1100 comprises a motion correction module 1106 that carries out the functions described herein with reference to repeatedly correcting motion effects during a scan, including any one of the intra-scan motion correction techniques described above.
  • the motion correction module 1106 may be executed on the computing system 1100 by a central processing unit 1102 discussed further below.
  • module refers to logic embodied in hardware or firmware, or to a collection of software instructions, possibly having entry and exit points, written in a programming language, such as, for example, COBOL, CICS, Java, Lua, C or C++.
  • a software module may be compiled and linked into an executable program, installed in a dynamic link library, or may be written in an interpreted programming language such as, for example, BASIC, Perl, or Python. It will be appreciated that software modules may be callable from other modules or from themselves, and/or may be invoked in response to detected events or interrupts.
  • Software instructions may be embedded in firmware, such as an EPROM.
  • hardware modules may be comprised of connected logic units, such as gates and flip-flops, and/or may be comprised of programmable units, such as programmable gate arrays or processors.
  • the modules described herein are preferably implemented as software modules, but may be represented in hardware or firmware. Generally, the modules described herein refer to logical modules that may be combined with other modules or divided into sub-modules despite their physical organization or storage.
  • the computing system 1100 also comprises a mainframe computer suitable for controlling and/or communicating with large databases, performing high volume transaction processing, and generating reports from large databases.
  • the computing system 1100 also comprises a central processing unit ("CPU") 1102, which may comprise a conventional microprocessor.
  • the computing system 1100 further comprises a memory 1104, such as random access memory (“RAM”) for temporary storage of information and/or a read only memory (“ROM”) for permanent storage of information, and a mass storage device 1108, such as a hard drive, diskette, or optical media storage device.
  • the modules of the computing system 1100 are connected to the computer using a standards based bus system.
  • the standards based bus system could be Peripheral Component Interconnect (PCI), MicroChannel, SCSI, Industrial Standard Architecture (ISA) and Extended ISA (EISA) architectures, for example.
  • PCI Peripheral Component Interconnect
  • ISA Industrial Standard Architecture
  • EISA Extended ISA
  • the computing system 1100 comprises one or more commonly available input/output (I/O) devices and interfaces 1112, such as a keyboard, mouse, touchpad, and printer.
  • the I/O devices and interfaces 1112 comprise one or more display devices, such as a monitor, that allows the visual presentation of data to a user. More particularly, a display device provides for the presentation of GUIs, application software data, and multimedia presentations, for example.
  • the I/O devices and interfaces 1112 also provide a communications interface to various external devices.
  • the computing system 1100 may also comprise one or more multimedia devices 1110, such as speakers, video cards, graphics accelerators, and microphones, for example.
  • the computing system 1100 may run on a variety of computing devices, such as, for example, a server, a Windows server, an Structure Query Language server, a Unix server, a personal computer, a mainframe computer, a laptop computer, a cell phone, a personal digital assistant, a kiosk, an audio player, and so forth.
  • the computing system 1100 is generally controlled and coordinated by operating system software, such as z/OS, Windows 95, Windows 98, Windows NT, Windows 2000, Windows XP, Windows Vista, Windows 7, Linux, BSD, SunOS, Solaris, or other compatible operating systems.
  • the operating system may be any available operating system, such as MAC OS X.
  • the computing system 5800 may be controlled by a proprietary operating system.
  • Conventional operating systems control and schedule computer processes for execution, perform memory management, provide file system, networking, and I/O services, and provide a user interface, such as a graphical user interface ("GUI”), among other things.
  • GUI graphical user interface
  • the computing system 1100 is coupled to a network 1116, such as a LAN, WAN, or the Internet, for example, via a wired, wireless, or combination of wired and wireless, communication link 1114.
  • the network 1116 communicates with various computing devices and/or other electronic devices via wired or wireless communication links.
  • the network 1116 is communicating with one or more computing systems 1118 and/or one or more data sources 1120.
  • Access to the image construction module 1106 of the computer system 1100 by computing systems 1118 and/or by data sources 1120 may be through a web-enabled user access point such as the computing systems' 1118 or data source's 1120 personal computer, cellular phone, laptop, or other device capable of connecting to the network 1116.
  • a web-enabled user access point such as the computing systems' 1118 or data source's 1120 personal computer, cellular phone, laptop, or other device capable of connecting to the network 1116.
  • Such a device may have a browser module is implemented as a module that uses text, graphics, audio, video, and other media to present data and to allow interaction with data via the network 1116.
  • the browser module may be implemented as a combination of an all points addressable display such as a cathode-ray tube (CRT), a liquid crystal display (LCD), a plasma display, or other types and/or combinations of displays.
  • the browser module may be implemented to communicate with input devices 1112 and may also comprise software with the appropriate interfaces which allow a user to access data through the use of stylized screen elements such as, for example, menus, windows, dialog boxes, toolbars, and controls (for example, radio buttons, check boxes, sliding scales, and so forth).
  • the browser module may communicate with a set of input and output devices to receive signals from the user.
  • the input device(s) may comprise a keyboard, roller ball, pen and stylus, mouse, trackball, voice recognition system, or pre-designated switches or buttons.
  • the output device(s) may comprise a speaker, a display screen, a printer, or a voice synthesizer.
  • a touch screen may act as a hybrid input/output device.
  • a user may interact with the system more directly such as through a system terminal connected to the score generator without communications over the Internet, a WAN, or LAN, or similar network.
  • the system 1100 may comprise a physical or logical connection established between a remote microprocessor and a mainframe host computer for the express purpose of uploading, downloading, or viewing interactive data and databases on-line in real time.
  • the remote microprocessor may be operated by an entity operating the computer system 1100, including the client server systems or the main server system, an/or may be operated by one or more of the data sources 1120 and/or one or more of the computing systems.
  • terminal emulation software may be used on the microprocessor for participating in the micro -mainframe link.
  • computing systems 1118 who are internal to an entity operating the computer system 1100 may access the image construction module 1106 internally as an application or process run by the CPU 1102.
  • a user access point or user interface 1112 comprises a personal computer, a laptop computer, a cellular phone, a GPS system, a Blackberry® device, a portable computing device, a server, a computer workstation, a local area network of individual computers, an interactive kiosk, a personal digital assistant, an interactive wireless communications device, a handheld computer, an embedded computing device, or the like.
  • the network 1116 may communicate with other data sources or other computing devices.
  • the computing system 1100 may also comprise one or more internal and/or external data sources.
  • one or more of the data repositories and the data sources may be implemented using a relational database, such as DB2, Sybase, Oracle, CodeBase and Microsoft® SQL Server as well as other types of databases such as, for example, a signal database, object- oriented database, and/or a record-based database.

Abstract

Systems, methods, and devices for intra-scan motion correction to compensate not only from one line or acquisition step to the next, but also within each acquisition step or line in k-space. The systems, methods, and devices for intra-scan motion correction can comprise updating geometry parameters, phase, read, and/or other encoding gradients, applying a correction gradient block, and/or correcting residual errors in orientation, pose, and/or gradient/phase.

Description

METHODS, SYSTEMS, AND DEVICES FOR
INTRA-SCAN MOTION CORRECTION
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. Provisional Application No. 61/527,972, filed August 26, 2011, and titled DYNAMIC ADJUSTMENT OF MAGNETIC FIELD GRADIENTS AND RF PULSES WITHIN MR SEQUENCES, which is hereby incorporated herein by reference in its entirety.
STATEMENT REGARDING FEDERALLY SPONSORED R&D
[0002] This invention was made with government support under Grant Number 5R01DA021146 awarded by the National Institutes of Health. The government has certain rights to this invention.
BACKGROUND
Field
[0003] This invention relates generally to the field of biomedical imaging, and more specifically to a system for correcting defects in medical images that are caused by a subject's movement during an in vivo (in the living body) magnetic resonance scan.
Description
[0004] "Tomographic" imaging techniques generate images of multiple slices of an object. Some commonly used tomographic imaging techniques include magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) techniques, which are ideal for assessing the structure, physiology, chemistry and function of the living brain and other organs, in vivo and non-invasively. Because the object of interest is often imaged in many scanning steps in order to build a complete two or three dimensional view, scans are of long duration, usually lasting several minutes. To increase resolution (detail) of a tomographic scan, more slices and more scanning steps must be used, which further increases the duration of a scan. Scans may also be of long duration in order to obtain sufficient signal-to-noise ratio. Magnetic resonance techniques (including tomographic techniques), that are currently known or to be developed in the future (hereinafter collectively referred to as "MR" or "MRI") can also afford relatively high spatial and temporal resolution, are noninvasive and repeatable, and may be performed in children and infants. However, due to their duration, MR scans can be subject to the problem of patient or object motion.
SUMMARY
[0005] Advancements in magnetic resonance technology make it possible to correct for artifacts in images obtained from magnetic resonance scans which are caused by motion of the subject during the magnetic resonance scan.
[0006] In some embodiments, a magnetic resonance system configured to correct intra-scan motion during a magnetic resonance scan comprises: a magnetic resonance scanner configured to generate a magnetic field gradient and a radiofrequency signal for the magnetic resonance scan; a motion tracking system configured to track one or more pose parameters of a subject and transmit pose data corresponding to the tracked one or more pose parameters at a given time to the magnetic resonance scanner; an electronic memory storage configured to store modules; and a computer processor configured to execute the modules comprising at least: a correction gradient calculation module configured to calculate a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the transmitted pose data and a gradient sequence used for the magnetic resonance scan; the magnetic resonance scanner further configured to apply the correction gradient to the subject prior to detecting signals emitted from the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan; and the magnetic resonance scanner further configured to detect the signals emitted from the subject for data acquisition.
[0007] In certain embodiments, an intra-scan motion correction system comprises: an electronic memory storage configured to store modules; and a computer processor configured to execute the modules comprising at least: a motion tracking module configured to receive pose data of a subject from one or more motion tracking systems during a magnetic resonance scan of the subject; and a correction gradient calculation module configured to calculate a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan.
[0008] In some embodiments, an intra-scan motion correction system comprises: an electronic memory storage configured to store modules; and a computer processor configured to execute the modules comprising at least: a motion tracking module configured to receive pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and an error correction module configured to calculate a gradient moment based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the calculated gradient moment, and wherein the one or more errors in the gradient moment are corrected during reconstruction.
[0009] In some embodiments, an intra-scan motion correction system comprises: an electronic memory storage configured to store modules; and a computer processor configured to execute the modules comprising at least: a motion tracking module configured to receive pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and an error correction module configured to calculate a phase based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the phase, and wherein the one or more errors in the phase are corrected during reconstruction.
[0010] In some embodiments, a computer-implemented method of correcting for intra-scan motion during a magnetic resonance scan comprises: generating by a magnetic resonance scanner a magnetic field gradient and a radiofrequency signal for the magnetic resonance scan; tracking by a motion tracking system one or more pose parameters of a subject and transmitting pose data corresponding to the tracked one or more pose parameters at a given time to the magnetic resonance scanner; calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the transmitted pose data and a gradient sequence used for the magnetic resonance scan; applying by the magnetic resonance scanner the correction gradient to the subject prior to detecting signals emitted from the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan; and detecting by the magnetic resonance scanner the signals emitted from the subject for data acquisition, wherein the computer comprises a computer processor and an electronic storage medium.
[0011] In certain embodiments, a computer-implemented method of correcting for intra- scan motion during a magnetic resonance scan comprises: receiving by a motion tracking module pose data of a subject from one or more motion tracking systems during the magnetic resonance scan of the subject; and calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan, wherein the computer comprises a computer processor and an electronic storage medium.
[0012] In some embodiments, a computer-implemented method of correcting for intra-scan motion during a magnetic resonance scan comprises: receiving by a motion tracking module pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and calculating by an error correction module a gradient moment based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the calculated gradient moment, and wherein the one or more errors in the gradient moment are corrected during reconstruction, wherein the computer comprises a computer processor and an electronic storage medium.
[0013] In some embodiments, a computer-implemented method of correcting for intra-scan motion during a magnetic resonance scan comprises: receiving by a motion tracking module pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and calculating by an error correction module a phase based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the phase, and wherein the one or more errors in the phase are corrected during reconstruction, wherein the computer comprises a computer processor and an electronic storage medium. [0014] In some embodiments, a computer-readable, non-transitory storage medium has a computer program stored thereon for causing a suitably programmed computer system to process by one or more computer processors computer-program code by performing a method to correct for intra- scan motion during a magnetic resonance scan when the computer program is executed on the suitably programmed computer system, wherein the method comprises: generating by a magnetic resonance scanner a magnetic field gradient and a radiofrequency signal for the magnetic resonance scan; tracking by a motion tracking system one or more pose parameters of a subject and transmitting pose data corresponding to the tracked one or more pose parameters at a given time to the magnetic resonance scanner; calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the transmitted pose data and a gradient sequence used for the magnetic resonance scan; applying by the magnetic resonance scanner the correction gradient to the subject prior to detecting signals emitted from the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan; and detecting by the magnetic resonance scanner the signals emitted from the subject for data acquisition, wherein the computer comprises a computer processor and an electronic storage medium.
[0015] In certain embodiments, a computer-readable, non-transitory storage medium has a computer program stored thereon for causing a suitably programmed computer system to process by one or more computer processors computer-program code by performing a method to correct for intra-scan motion during a magnetic resonance scan when the computer program is executed on the suitably programmed computer system, wherein the method comprises: receiving by a motion tracking module pose data of a subject from one or more motion tracking systems during the magnetic resonance scan of the subject; and calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan, wherein the computer comprises a computer processor and an electronic storage medium.
[0016] In some embodiments, a computer-readable, non-transitory storage medium has a computer program stored thereon for causing a suitably programmed computer system to process by one or more computer processors computer-program code by performing a method to correct for intra- scan motion during a magnetic resonance scan when the computer program is executed on the suitably programmed computer system, wherein the method comprises: receiving by a motion tracking module pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and calculating by an error correction module a gradient moment based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the calculated gradient moment, and wherein the one or more errors in the gradient moment are corrected during reconstruction, wherein the computer comprises a computer processor and an electronic storage medium.
[0017] In some embodiments, a computer-readable, non-transitory storage medium has a computer program stored thereon for causing a suitably programmed computer system to process by one or more computer processors computer-program code by performing a method to correct for intra-scan motion during a magnetic resonance scan when the computer program is executed on the suitably programmed computer system, wherein the method comprises: receiving by a motion tracking module pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and calculating by an error correction module a phase based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the phase, and wherein the one or more errors in the phase are corrected during reconstruction, wherein the computer comprises a computer processor and an electronic storage medium.
[0018] For purposes of this summary, certain aspects, advantages, and novel features of the invention are described herein. It is to be understood that not necessarily all such advantages may be achieved in accordance with any particular embodiment of the invention. Thus, for example, those skilled in the art will recognize that the invention may be embodied or carried out in a manner that achieves one advantage or group of advantages as taught herein without necessarily achieving other advantages as may be taught or suggested herein.
BRIEF DESCRIPTION OF THE DRAWINGS
[0019] The foregoing and other features, aspects and advantages of the present invention are described in detail below with reference to the drawings of various embodiments, which are intended to illustrate and not to limit the invention. The drawings comprise the following figures in which:
[0020] FIG. 1A depicts an example illustrating the effects of motion of a subject during a magnetic resonance scan by a conventional MRI system.
[0021] FIG. IB depicts an example illustrating the effects of motion of a subject during a magnetic resonance scan by an adaptive MRI system.
[0022] FIG. 2 illustrates the effects of motion of a subject during a magnetic resonance scan in k-space.
[0023] FIG. 3 depicts an example of one embodiment of an intra-scan motion correction system coupled with a magnetic resonance scanner.
[0024] FIG. 4 is a time frame diagram illustrating an example of embodiments of one or more methods of intra-scan motion correction during a magnetic resonance scan.
[0025] FIG. 5 is a process flow diagram illustrating an example of an embodiment of an update geometry parameters block of an embodiment of a method of intra- scan motion correction during a magnetic resonance scan.
[0026] FIG. 6 is a process flow diagram illustrating an example of an embodiment of an update phase and/or read encoding gradient(s) block of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan.
[0027] FIG. 7 is a process flow diagram illustrating an example of an embodiment of an apply correction gradient block of an embodiment of a method of intra- scan motion correction during a magnetic resonance scan.
[0028] FIG. 7A is a process flow diagram illustrating an example of an embodiment of an apply correction phase block of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan. [0029] FIG. 8 is a process flow diagram illustrating an example of an embodiment of an error correction block of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan.
[0030] FIG. 9 is a schematic diagram illustrating the effects of an example of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan.
[0031] FIG. 10 is a schematic diagram illustrating the effects of an example of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan.
[0032] FIG. 11 is a block diagram depicting one embodiment of a computer hardware system configured to run software for implementing one or more embodiments of the continuous intra-scan motion correction systems described herein.
DETAILED DESCRIPTION
[0033] Embodiments of the invention will now be described with reference to the accompanying figures. The terminology used in the description presented herein is not intended to be interpreted in any limited or restrictive manner, simply because it is being utilized in conjunction with a detailed description of certain specific embodiments of the invention. Furthermore, embodiments of the invention may comprise several novel features, no single one of which is solely responsible for its desirable attributes or which is essential to practicing the inventions herein described.
[0034] The disclosure herein provides methods, systems, and devices for intra- scan motion correction during a magnetic resonance (MR) scan.
[0035] As used herein, the terms "magnetic resonance techniques," "magnetic resonance imaging," "magnetic resonance scan," "MR techniques," "MR imaging," "MR scan" are broad interchangeable terms, and comprise without limitation magnetic resonance scan, magnetic resonance imaging, functional magnetic resonance imaging, diffusion magnetic resonance imaging, magnetic resonance tomographic techniques, magnetic resonance spectroscopy, other magnetic resonance-based techniques currently existing or to be developed in the future, and/or combinations thereof.
[0036] Further, as used herein, the terms "intra-scan motion correction," "intra- sequence motion correction," "continuous intra-scan motion correction," "substantially continuous intra-scan motion correction," "nearly continuous intra-scan motion correction," "repeated intra-scan motion correction," "rapidly repeated intra-scan motion correction," and "quasi-continuous intra-scan motion correction" are broad interchangeable terms, and comprise without limitation single, one or more, continuous, quasi-continuous, substantially continuous, nearly continuous, repeated corrections or the like for one or more errors due to motion of a subject during a magnetic resonance scan, wherein the corrections are applied during the magnetic resonance scan for any magnetic resonance techniques. In addition, as used herein, the terms "real time," "near real time," and "substantially real time" are broad interchangeable terms, and comprise without limitation real time, near real time, or substantially real time periods with minimal delay or lag, for example instantaneously, within 20-30 milliseconds, and/or within 2-3 seconds or longer.
[0037] Because certain magnetic resonance techniques require that so many measurements be taken (because so many slices and/or scanning steps are necessary), MR scans typically have a long duration, so that motion of the subject is a substantial problem for acquiring accurate data. Consequently, subjects commonly are required to lie still to within one millimeter and one degree (better than the image resolution) over extended time periods. These strict requirements cannot be met by many subjects in special populations, such as children and infants, patients with stroke, head trauma, dementia, very sick patients, subjects who are agitated or delirious perhaps due to anxiety or drug use, animals, or patients with movement disorders, resulting in data with motion artifacts. As a result, in order to perform an MR scan in such subjects, anesthesia can be required. However, anesthesia can cost about $900 and also has roughly 1/250,000 risk of death.
[0038] Further, many tomographic imaging techniques rely on detecting very small percentage changes in a particular type of signal, which makes these techniques even more susceptible to movement. In functional magnetic resonance imaging, for example, changes in the properties of blood in brain areas activated while subjects are performing tasks causes small signal changes (on the order of a few percent) that can be detected with MR. However, these small signal changes may easily be obscured by signal changes of similar or even greater size that occur during unintentional subject movements.
[0039] The basic problem is that it may take several minutes for a scan to be completed, but the patient or other object being scanned cannot remain sufficiently still for several minutes. Further, the space for a patient or other object being scanned (the "scanning volume") in an MR machine is very limited - there is very little space in an MR machine once a patient has been positioned inside for a scan. The motion during the scan of a single dataset (e.g. spectrum, 2D-slice, multiple slices or 3D-volume) causes the single acquisition steps to become inconsistent. Since the resulting data are reconstructed from many acquisition steps, this inconsistency can lead to significant data errors, called motion artifacts.
[0040] For example, at any given hospital or medical facility, 1 out of every 25 brain examinations can be lost entirely and 1 out of 2 examinations can require at least one repeat scan. The total economic loss to hospital in the U.S. due to such motion artifacts is estimated to be roughly 1.5 million hours per year or $1 billion annually at $750 per hour.
[0041] However, by implementing one or more methods, systems, and devices for intra-scan motion correction as described herein, subjects of a magnetic resonance scan are not required to lie still. Rather, because the methods, systems, and devices for intra-scan motion correction as described herein are able to account for movements in subjects of varying degrees and speed, substantially any movement by a subject during a magnetic resonance scan. In some embodiments, substantially any movement by a subject that can be approximated by a local rigid body motion and/or nearly rigid body motion in the area or object of interest can be accounted for. In certain embodiments, any motion of a subject or within a subject that can be described by a motion path that can be approximated by a rigid body can be take into account.
[0042] In some embodiments, the methods, systems, and devices for intra-scan motion correction can allow for magnetic resonance scan techniques, whether existing now or to be developed in the future, to be applied to many subjects, including those in special populations, such as children, infants, very sick patients, subjects who are agitated perhaps due to anxiety or drug use, or patients with movement disorders. In addition, effects of movements of certain objects located within a subject, such as internal organs of a subject, fetus, or the like, can also be corrected for in certain embodiments. Further animals may also be subjected to a magnetic resonance scan by implementing one or more methods, systems, and devices for intra-scan motion correction as described herein. Additionally, inanimate objects that move, including flowing liquids or gases, may also be subjected to a magnetic resonance scan by implementing one or more methods, systems, and devices for intra-scan motion correction as described herein. In addition, the methods, systems, and devices for intra-scan motion correction can substantially reduce the economic loss described above due to motion artifacts.
[0043] In addition, in some embodiments, the methods, systems, and devices for intra-scan motion correction as described herein do not require that gradients track the rotation of the object of interest as other certain embodiments do or attempt to do. Rather, in some embodiments of the methods, systems, and devices for intra-scan motion correction as described herein, gradient rotations are specifically not updated within a single scan (between excitation and data acquisition). In other words, gradients remain stationary and do not track the motion of the subject to be scanned in some embodiments. The result is that at the end of the sequence, the Bloch equations governing magnetic resonance are not satisfied in some situations, which can introduce an error in the gradient moment. Some embodiments of the methods, systems, and devices for intra-scan motion correction as described herein can unexpectedly eliminate such error in the gradient moment by applying a single, brief, correction gradient of proper gradient moment prior to data acquisition.
[0044] Further, in general, subject movement can comprise rotations and/or translations. Rotation matrices can be non-linear, due to the presence of sine and cosine terms. Therefore, if the Bloch equations are violated in some embodiments by not having gradients track subject movement, one might expect that the resulting phase errors become "non-linear" in space, and consequently cannot be corrected using linearly varying gradients. However, theoretical analysis demonstrates that one can use linear gradients to correct the resulting. Accordingly, in some embodiments, the methods, systems, and devices for intra- scan motion correction as described herein can correct for motion artifacts not only due to translations, but also due to small and/or large rotations without having gradients track subject movement.
[0045] Moreover, some embodiments of the methods, systems, and devices for intra-scan motion correction as described herein can be simple and not require a substantial amount of data processing. For example, in some embodiments, only one or more additional processes are required in addition to a general magnetic resonance scan process in order to correct for subject motion during the magnetic resonance scan. Accordingly, implementation of some embodiments of the methods, systems, and devices for intra-scan motion correction as described herein can be relatively easy and can be implemented in conjunction any and/or all existing magnetic resonance scan equipment and/or those to be developed in the future. Accordingly, the methods, systems, and devices for intra-scan motion correction as described herein can provide an unexpectedly simple yet accurate correction for any and/or all types of subject motion during a magnetic resonance scan.
Reducing Sensitivity of Scans to Motions of Subject
[0046] In some embodiments, specially designed scan sequences can be utilized to minimize the effects of constant motion during a single acquisition step without relevant organ shift during the entire acquisition. For example, a first order flow compensation can be utilized. While such embodiments are particularly useful for reducing artifacts or imaging errors due to flowing blood they are not particularly useful in correcting movements of entire organs, such as head movements.
[0047] In other embodiments, improved sampling schemes for the magnetic resonance data can be used to reduce sensitivity to motion. Such embodiments can reduce motion sensitivity of magnetic resonance scans under certain conditions. However, they are not particularly useful in correcting motions under other conditions or for very quick movements. Further such embodiments can require redundant measurements to encode additional information required for correction and thus reduce sampling efficiency. Such embodiments are also not generally applicable to all measurement techniques.
[0048] In certain embodiments, certain ultra-fast single shot imaging techniques can be utilized to account for movement by a subject during a magnetic resonance scan. For example, echo planar imaging, spiral imaging, or imaging using other fast trajectories can be utilized. In such embodiments the entire organ of interest, such as a brain, is scanned continuously every few seconds over the course of minutes, for instance, for functional magnetic resonance imaging, diffusion imaging, perfusion imaging, or other modalities. By doing so, such embodiments make it possible to determine the pose defined as a position and rotation, for example of the head or other subject at each instant relative to the initial pose, using image -based registration and/or alignment of images. More specifically, once the pose for a given instant is known relative to the initial image, the magnetic resonance scanner's image for that instant can be realigned to the initial image. Further, realignment of magnetic resonance imaging volumes comprising multiple slices can be used to correct for head motion and functional magnetic resonance imaging time series. However, such embodiments are inherently slow because they use magnetic resonance imaging and may be unable to correct for motion in certain directions, such as orthogonal to the scan planes or towards or away from the planes in which the scans are being taken. Also, such embodiments correct movements only every few seconds (for each volume).
Motion Correction Methods
[0049] The embodiments for reducing sensitivity of scans to motions of a subject described above, however, are rather limited. One major problem is related to the manner in which typical tomographic imaging methods acquire data. Specifically the data for each cross section or slice is acquired by moving step by step along lines in a mathematical space, also known as k-space. This data acquisition step is typically repeated hundreds of times in a magnetic resonance imaging scan, until all lines in the k-space have been filled. For three dimensional imaging, thousands of such steps are required to acquire an entire volume. The various embodiments of reducing sensitivity of scans to subject motion , however, typically do not account for variations in the subject's pose amongst the different k-space lines, even though motion sensitivity for each individual acquisition or a line in k-space is reduced. Further, the various embodiments of reducing sensitivity of scans to motions of a subject rather poorly tolerate fast or irregular movements within individual acquisition steps.
[0050] Accordingly, in some embodiments, the pose of the subject of the scan and motion is tracked near-real time, during a scan. For example, the subject can be a head, brain, or other organ of interest or other object. The pose information that is tracked can be used to compensate for the detected motion in data acquisitions for subsequent acquisition steps or slices or volumes within the same scan. Such embodiments can be denoted "prospective motion correction" because the acquisition steps are adapted prospectively during the scan to compensate for the motion detected.
[0051] One important aspect of such embodiments of adapting imaging by prospective motion correction is the accuracy or resolution of the motion tracking system. Because of the high resolution generally required for biomedical imaging, the motion tracking system in such embodiments must also have a high resolution, because the motion tracking system's information will be used to align the various acquisition steps. Accordingly, if the motion tracking system's resolution is high enough, all of the acquisition steps can be accurately aligned or registered despite a subject's motion. Conversely, if the motion tracking system's resolution is not high enough, the acquisition steps will not be accurately aligned or registered.
[0052] In some embodiments of adapting imaging by prospective motion correction magnetic resonance "navigator" signals can be utilized to estimate the pose of the subject and to dynamically correct for the subject's motion. Further, a magnetic resonance based navigator can also be utilized for adaptive motion correction in magnetic resonance imaging. In other embodiments, small radiofrequency coils can be utilized to track catheters during interventional magnetic resonance imaging.
[0053] While such embodiments of magnetic resonance based adaptive magnetic resonance imaging techniques provide good or satisfactory results in many situations, they intrinsically interfere with the magnetic resonance acquisition process. Further, such embodiments can work only for a limited number of magnetic resonance sequences and can be limited to measuring the position or pose of a subject a few times per second at best.
[0054] Accordingly, in some embodiments, external or non-magnetic resonance based techniques can be utilized to track subject motion rather than magnetic resonance based methods. For example, one or more optical methods can be utilized. In some embodiments, the pose information from the tracking system can be sent to the magnetic resonance scanner and be used by the scanner to compensate for the motion in subsequent acquisition steps.
[0055] In some embodiments, stereovision can be utilized to track the motion of a subject, for example by using two or more cameras and multiple, at least two markers. In other embodiments, accurate tracking of the subject, for example the head or brain or other organ, can be achieved using a single camera and a special marker in the magnetic resonance environment. For example, the special marker can be a self -encoded marker, a retrograde reflector or RGR or Moire Phase Tracking target. Optical systems can provide accurate, non- contact sensing with a passive and non-magnetic target and can also provide fast pose updates on the order of 100 to 1,000 poses per second or even faster.
[0056] In some embodiments pose data from the tracking system are sent in near real time to a magnetic resonance scanner, which then nearly continuously updates scan parameters prior to each acquisition step or line in k-space. This way, the scan planes are locked relative to the moving object of interest. Images acquired with such embodiments of prospective motion correction can show substantially reduced motion artifacts compared to images acquired without motion correction.
[0057] However, in some situations pose data as received by the magnetic resonance scanner may be imperfect, for example due to inaccuracies or noise in the tracking system or due to lag times between the marker movement and arrival of tracking data on the scanner. In order to correct for such inaccuracies or delays, some of these inaccuracies or delays can be determined after the magnetic resonance scan has been acquired in certain embodiments as the entire tracking data are then available. More specifically, when prospective motion correction is applied, subject motion between the pose detection and magnetic resonance data acquisition can occur due to the time required to acquire and transfer marker images to the tracking computer, calculate pose information, perform magnetic resonance sequence updates, and the intrinsic timing of the sequence. Accordingly, differences between the assumed or estimated pose and the true pose during the acquisition step may cause residual motion artifacts. Similarly, inaccuracies in the tracking system, such as tracking noise, can cause errors. However, in certain embodiments some of these effects of tracking errors on magnetic resonance signals can be corrected retrospectively within the data reconstruction by comparing the estimated or assumed pose from the tracking system and the true pose that is available after the acquisition step.
[0058] The shortcomings of such embodiments of non-magnetic resonance correction methods and others, however, are related to the fact that such embodiments use updates of scan parameters once prior to each magnetic resonance acquisition step or line in k-space. In fact, magnetic resonance acquisitions involve a sequence of events. For example, a common sequence involves excitation of the spin system using one or more radiofrequency pulses, possibly slice selective, spatial encoding using spatially variable switched magnetic fields (gradients), possible further manipulations of the spin system such as rephasing and complementary information encoding steps, and data acquisition. For some sequences, excitation may be preceded by an extra module to prepare the spin system to achieve a certain contrast. As a result, acquisition of a single k-space line may last a few milliseconds to several hundred milliseconds. However, pose updates for prospective motion correction embodiments above have been applied immediately prior to excitation for each individual magnetic resonance acquisition or k-space line. Consequently, pose updates may be applied approximately ten times per second, even if the tracking system is capable of tracking at a higher rate, for example at 100 poses per second.
[0059] The scheme described above of updating scan parameters once per individual acquisition step or k-space line can provide adequate motion correction if the object of interest does not move too fast. However, if the motion of the subject within an individual acquisition step becomes too fast, then additional motion artifacts may be generated in the resulting images, which cannot be corrected with once per acquisition pose updates. Such motion can be denoted "intra-scan motion."
[0060] Accordingly, in some embodiments, motion artifacts due to substantial intra-scan motion can be eliminated or attenuated by attempting to nearly continuously update magnetic field gradients and radiofrequency pulses during each acquisition. This way their orientation is perfectly aligned with the moving object of interest at any time. For example, such an embodiment can be implemented for diffusion-weighted magnetic resonance imaging, which involves very strong magnetic field gradients and is particularly sensitive to subject motion. In certain embodiments, a single magnetic resonance acquisition step, which typically involves a single sequence block of approximately 100 milliseconds for its application, can be broken down into multiple separate blocks, each lasting approximately two milliseconds. The direction of gradients for each of these two millisecond blocks can be updated using the most recent tracking data, resulting in a quasi-continuous pose update during the acquisition.
[0061] Despite the features of embodiments of quasi-continuously updating parameters during each acquisition as described above, implementation of such a quasi- continuous pose date scheme is extremely challenging and may not be possible on all available magnetic resonance scanner platforms. In addition, an ideal implementation of such embodiments of quasi-continuous correction methods during each acquisition would necessarily require that updates are made continuously. In contrast, current magnetic resonance scanners cannot update gradient orientations continuously. As such, pose updates can be applied only quasi-continuously, for example every two milliseconds. Consequently, it would be advantageous to have a simpler scheme to correct for intra-scan movements that does not rely on ideally continuous updates of measurement parameters. Intra-Scan Motion Correction - Introduction
[0062] As generally described above, movement by a subject during a magnetic resonance scan can present significant problems in obtaining clear images of the subject. The effects of motion of a subject during a magnetic resonance scan are illustrated in Figures 1A and IB. Figure 1A illustrates the effects of a subject's motion during a magnetic resonance scan by a conventional magnetic resonance scanner. As illustrated in Figure 1A, if a subject of a magnetic resonance imaging scan, such as a head, is titled to a certain degree, the resulting slice or image from that scan, which is stationary, inevitably becomes tilted relative to the subject as well. Such movement by the subject during a scan can result in blurry and/or unclear images. As a result, the acquired magnetic resonance scan may not be useful to a medical professional or the subject may be required to redo the entire magnetic resonance scan, resulting in an unnecessary burden in time and cost.
[0063] However, by utilizing one or more intra-scan motion correction methods described herein, the geometry and/or phase of a signal can be updated periodically and/or prospectively during a scan to substantially match the motion of the subject. Figure IB illustrates the effects of a motion of a subject during a magnetic resonance scan by an intra- scan motion correction system. As illustrated in Figure IB, as the subject, or head in this example, is tilted or moved, the slice plane of the magnetic resonance scanner and/or phase and/or read orientations can also be tilted and/or adjusted to account for the motion of the subject. This way, any or substantially all of the subject's movement can be accounted for, resulting in a clean image that is substantially similar to an image that would have been acquired if the subject had not moved at all. Accordingly, by utilizing one or more methods, systems, and devices for an intra-scan motion correction as described herein, a subject of a magnetic resonance imaging scan can be allowed to move with attenuated and/or without any such detrimental effects to the imaging results.
[0064] In general, slow motions of a subject during a magnetic resonance scan can be defined as movements with speeds of about 1 mm/sec or 1 degrees/sec. Such slow motions can comprise slow drifts and can be nearly imperceptible. Moderate motions of a subject during a magnetic resonance scan can be defined as movements with speeds of about 10 mm/sec or 10 degrees/sec. Such moderate motions are perceptible and can be common in children and sick or confused patients. Fast motions of a subject during a magnetic resonance scan can be defined as movements with speeds of about 100 mm/sec or 100 degrees/sec or faster. Such fast motions can occur due to coughing or extreme agitation and can be limited in range and duration, for example 100 ms, due to confined space.
[0065] In some embodiments of methods, systems, and devices for intra-scan motion correction as described herein, motion artifacts arising from slow and moderate motions can be accounted for. In certain embodiments of methods, systems, and devices for intra-scan motion correction as described herein, even motion artifacts arising from fast motions can also be accounted for.
[0066] In general, some effects of motion on moving spins can comprise unwanted phase shifts between excitation and signal readout, unwanted pose changes between phase-encoding steps (or lines in k-space), and uncorrected pose changes between successive slices or volumes. Uncorrected pose changes between successive slices or volumes can occur in ultra-fast acquisitions that image the entire subject or brain every few seconds. Such volumes can be translated and rotated. Unwanted pose changes between phase encoding steps can result in blurring; in other words, the object of interest can be imaged at variable poses. Lastly, unwanted phase shifts between excitation and signal readout can result in artifacts in the phase-encoding direction after image reconstruction. The unwanted pose changes and uncorrected pose changes are purely geometric and thus can relatively easily be corrected. However, correcting phase shifts can be more complicated.
[0067] Generally, the magnetic resonance scanner detects the sum of magnetization of the individual spins in a given volume. The sum of signals from all individual spins is detected. In order for the magnetic resonance signal to be detectable, phases of individual spins need to be coherent or aligned. Loss of phase coherence of spins can cause signal attenuation or loss. In order to ensure phase coherence during signal detection, gradients have to be balanced throughout a pulse sequence, because gradients affect a spin's frequency and phase dependent on the spin's spatial position. Furthermore, the phase of the signals detected has to be aligned across acquisition steps or lines in k-space. However, motion interferes with this process by inducing unintended phase shifts. Accordingly, motion artifacts caused by phase shifts can be corrected if the phase shifts can be accounted for. [0068] In order to account for a subject's motion during a magnetic resonance scan the motion of the object of interest can first be characterized mathematically. The object of interest can be assumed for example to be a rigid body. Mathematically, the pose of the object can be characterized by six time dependent parameters, three translations and three rotations. In other words, a pose of an object can be considered to comprise six degrees of freedom. In contrast, orientation of an object can comprise two or more degrees of freedom, three or more degrees of freedom, four or more degrees of freedom, or five or more degrees of freedom.
[0069] The 3 translations can form a translation vector X( t) and the 3 rotations can form a rotation matrix R(t), where t represents time. The trajectory of a spin (initial vector position x0) inside the imaging volume can then described by the vector equation: x(i) = X (t) + R(t) xo .
[0070] As described above, a magnetic resonance sequence generally involves a series of radiofrequency pulses, switched magnetic field gradients, and one or more acquisition events. For simplicity, a sequence involving a single excitation radiofrequency pulse (at time t=0), followed by a time series of gradients [denoted by vector G(t)] and data acquisition can be considered. Motion within this sequence ("intra-scan motion") alters both the zero-order phase (due to translations) and effective gradient moment M (due to rotations) in the object coordinate system.
[0071] Translations X( t) will cause a change in the overall phase φ of the object at the time T of data acquisition, and rotations R(t) will cause a change in the gradient moment M of the object at the time T of data acquisition. It can be shown that the effects of translations and rotations are as follows:
T
Figure imgf000021_0001
where time t=0 denotes excitation of the spin system and γ is the gyro magnetic ratio. For a stationary object (R(t)= 1), equation 1 reduces to: τ
statiomry = { G( - ^ = 0
0
which equals zeiu since magnetic resonance sequences are generally balanced (first gradient moment between excitation and data acquisition is zero). However, time-dependent rotations induce a gradient imbalance (residual gradient moment M as per Eq. 1) that can result in signal attenuation or dropouts in the presence of sufficiently strong motion. Additionally, since gradient moments are used for spatial encoding, motion-dependent alterations in gradient moments can alter the spatial encoding of magnetic resonance signals and cause artifacts during image reconstruction. Likewise, time dependent translations can induce a spatially constant phase as per Eq. 2 that can vary from one acquisition step to another and can lead to artifacts in the reconstructed data.
[0072] These phase and gradient moment effects caused by intra- scan motion arise from the interaction between the moving object and switched magnetic field gradients. However, most embodiments of non-continuous motion correction methods consider only geometric effects of motion, such as ensuring that scan planes are aligned correctly during scans (see, for example, FIGURE IB), with the exception of the quasi-continuous embodiment described above. However, the geometric effects and phase/gradient moment effects are conceptually entirely different. For instance, phase effects may occur even if all geometric effects are corrected, and vice versa. Accordingly, in order to accurately correct for movement and/or motion of a subject during a magnetic resonance scan, both geometric effects and phase/gradient moment effects must be accounted for.
[0073] Figure 2 illustrates the phase/gradient movement effects in generating a magnetic resonance image via k-space when the subject moves in orientation and/or pose. When a subject of a magnetic resonance scan remains completely still and does not move, the data acquired from such scan is generally placed in the correct position of k-space which is denoted by the intersection between the center vertical line and one or more solid horizontal lines as depicted in Figure 2. However, when the subject of a magnetic resonance scan moves, the data acquired cannot be placed in the correct k-space either vertically and/or horizontally. Vertical displacement, or placing an acquired data off of a horizontal parallel line, denotes an error in the phase encoding. Horizontal displacement, or placing an acquired data off of the center vertical line, denotes an error in the read encoding or frequency encoding. In other words, the x axis in k-space is encoded by a read gradient, and the y axis in k-space is encoded by a phase gradient. As such, the phase encoding gradient, or the read encoding gradient, or both the phase encoding gradient and the read encoding gradient must be updated according to the detected motion of the subject in order to account for substantially all motion effects by the subject during the scan. Further, rotations in space generally correspond to rotations in k-space. Therefore, rotations of the subject may be corrected by adjusting phase encoding gradients and/or frequency encoding gradients so that they match the rotation of the subject to be scanned. In some embodiments , translations of the subject can essentially be approximated by phase shifts that vary linearly in k-space and corrected for intra-scan or during image reconstruction.
Intra-Scan Motion Correction - System Overview
[0074] As described above because both geometric and phase/gradient movement effects must be accounted for in order to better correct motion of a subject during a magnetic resonance scan, embodiments of the intra-scan motion correction systems, methods, and devices described herein comprise one or more techniques of targeting these effects. Also, embodiments of the intra-scan motion correction systems, devices, and methods described herein generally use less data processing capabilities compared to the quasi-continuous embodiment described above and can be utilized with the majority of currently available magnetic resonance scanners. Additionally, prospective update errors due to the inherent lag time, noise, or the like in the quasi-continuous correction embodiment described above can be eliminated in embodiments of the intra-scan motion correction system, methods, and devices described herein.
[0075] Figure 3 illustrates an embodiment of a system for intra-scan motion correction. An intra-scan motion correction system can be configured to be used in conjunction with one or more magnetic resonance scanners. In some embodiments, a magnetic resonance scanner can comprise an intra-scan motion correction system. In other embodiments, a magnetic resonance scanner and an intra-scan motion correction system are physically separate. In certain embodiments, one or more parts or modules of a magnetic resonance scanner and an intra-scan motion correction system are shared and/or accessible by the other. [0076] As illustrated in Figure 3, an embodiment of an intra-scan motion correction system can generally comprise a main computing system 300, a user interface 302, and a display for outputting constructed images 334. In some embodiments, the user interface 302 can allow a medical professional and/or other user to control the intra-scan motion correction system and/or magnetic resonance system, such as turning the system on or off and/or controlling one or more parameters of the system. By utilizing the user interface 302, a user can instruct the main computing system 300 to turn a magnetic field gradient 304 on or off by transmitting the instruction from the main computing system 300 to a magnetic field gradient generator 304. In addition a user can use the user interface 302 to instruct the main computing system 300 to turn a radiofrequency signal generator 306 on or off and also control the radiofrequency signal generator 306 to emit a radiofrequency signal of a certain type.
[0077] The motion tracking system 310 can track substantially any and all motion of the subject 308 during a magnetic resonance imaging scan. The motion tracking system 310 can comprise any of the motion tracking systems that are currently known or to be developed in the future. For example, the motion tracking system 310 can be an optical or stereo vision system (in-bore or out-bore), optical system with multiple cameras (in-bore or out-bore), laser-based tracking system with or without a reflector (in-bore or out-bore), radiofrequency pickup coils-based system (in-bore), magnetic field gradient monitoring system (in-bore), wire loop recordings-based system (for example, using EEG equipment), self-encoded marker-based system, single camera-based system (in-bore or out-bore), mechanical detection system, magnetic field gradient monitoring-based system, ultrasound- based system, or the like. After the motion tracking system 310 tracks the motion of the subject 308, the tracking data can be transmitted from the motion tracking system 310 to the main computing system 300. In some embodiments, the motion tracking system 310 is configured to track and/or send data related to the motion of the subject 308 in real time.
[0078] In some embodiments the motion tracking data that is collected by the motion tracking system 310 is transmitted to the main computing system 300 over a computer network periodically in packets of data. In other embodiments the motion tracking data collected by the motion tracking system 310 is transmitted over a computer network to the main computing system 300 at once in a relatively large data packet. [0079] The magnetic field gradient and/or radiofrequency signals that are generated by the magnetic field gradient generator 304 and radiofrequency signal generator 306 respectively can affect the magnetization of one or more nuclei of the subject 308. By manipulating the magnetic field gradient and radiofrequency signal, such generated magnetization can be further manipulated in the subject 308, resulting in a signal emission from the subject 308. The emitted signal can be detected by one or more magnetic resonance detector devices and/or receivers 312. Such detected data by the magnetic resonance detector device and/or receiver can be transmitted over a computer network or another connection to the main computing system 300.
[0080] The data transmitted from the motion tracking system 310 to the main computing system 300 can be further processed by the motion tracking module 314. For example, the motion tracking module 314 can be configured to generate a motion trajectory of the subject 308. Any such motion data that is transmitted from the motion tracking system 310 and/or motion data that is further processed by the motion tracking module 314 can be stored in a database 332 of the main computing system 300.
[0081] Based on the detected motion data by the motion tracking system 310, a geometry update module 316 can be configured to update and/or adjust one or more geometric parameters accordingly in order to compensate for the subject's motion. Any or all geometric parameter updates by the geometry update module 316 can further be stored in the database 332 of the main computing system 300.
[0082] Further, based on the detected motion data by the motion tracking system 310, a phase encoding update module 318 can be configured to update one or more phase encoding gradients. The phase encoding gradient updates that are processed by the phase encoding update module 318 can further be stored in the database 332 of the main computing system 300.
[0083] In addition, a read encoding gradient update module 320 can be configured to update one or more read encoding gradients based on the motion of the subject 308 as detected by the motion tracking system 310. The read encoding gradient updates that are processed by the read encoding update module 320 can further be stored in the database 332 of the main computing system 300. [0084] The main computing system 300 can further comprise a magnetic resonance sequence module 324. The magnetic resonance sequence module 324 can be configured to process a particular magnetic resonance sequence or a series thereof for one or more magnetic resonance scans. The processed magnetic resonance sequence can be generated by the magnetic field gradient generator and/or radiofrequency signal generator 306 and applied to a subject 308. The magnetic resonance sequence module 324 can further be configured to track or log one or more magnetic resonance sequences, which can then be stored in the database 332 of the main computing system 300.
[0085] Further, a correction gradient calculation module 326 of the main computing system 300 can be configured to calculate a first gradient moment during one or more magnetic resonance scans. More specifically, in certain embodiments, the correction gradient calculation module 326 is configured to calculate the (first) gradient moment according to Equation 1 and using the tracked pose and/or orientation data and a gradient signal and/or sequence used during one or more scans. The (first) gradient moment is the time integral of the gradient waveform. In other words, the (first) gradient moment is the area beneath the gradient waveform when plotted against time. In certain embodiments, the gradient waveform can be triangular, trapezoidal, sinusoidal or the like in shape. In other certain embodiments, the gradient waveform may be a superposition of a non-corrected gradient waveform with a triangular, trapezoidal, sinusoidal, waveform or the like in shape. In some embodiments, the only property of the gradient waveform that is required in a method for intra-scan motion correction is the first gradient moment according to Equation 1.
[0086] As discussed above, it is a motion-induced alteration in this gradient moment that can cause phase-based motion artifacts in magnetic resonance scans. Accordingly, in some embodiments, a correction gradient or a "blip" gradient can be applied to the subject 308 in order to counteract and/or reverse the effects of the altered first gradient moment. As such, in certain embodiments, the correction gradient calculation module 326 is further configured to determine an appropriate correction gradient moment to be applied to the subject 308. The appropriate correction gradient moment can be equal to the first gradient moment in absolute value but with an opposite sign from the first gradient moment according to Equation 1. In other words, by applying a correction gradient with a moment of -M, motion artifacts caused by a gradient moment of M can be accounted for and the signal phase can be corrected.
[0087] In certain embodiments, a correction gradient of a moment as determined by the correction gradient calculation module 326 can be applied to a subject 308 by a magnetic field gradient generator 304. Further, in some embodiments, the (first) gradient moment and/or correction gradient moment that is calculated can be stored in a database 332 of the main computing system 300.
[0088] In some embodiments, a phase correction module 328 can be configured to correct errors in one or more constant phases due to subject motion (according to equation 2) prior to data acquisition, during data acquisition, and/or during the reconstruction process of the image. In certain embodiments, the phase correction module 328 is configured to correct errors based on the tracked pose data and/or Equation 2. The phase corrections that are processed by the phase correction module 328 can further be stored in the database 332 of the main computing system 300.
[0089] Additionally, the main computing system 300 can also comprise an error correction module 330. The error correction module 330 can be configured to identify and correct any residual errors that remain after data acquisition. For example, the error correction module 330 can be configured to identify and/or correct errors in orientation, pose, and/or phase. In some embodiments, the error correction module 330 can be configured to correct one or more residual errors in one or more geometry parameters and/or signal phase and/or first gradient moment that are present after applying or without applying one or more geometry updates, phase encoding updates, read encoding gradient updates, and/or application of an additional magnetic moment correction gradient. For example, the error correction module 330 can be configured to retrospectively correct errors in one or more geometry parameters, gradient moment, and/or phase.
[0090] In certain embodiments, the error correction module 330 can be configured to correct for one or more errors due to lag time in obtaining and processing orientation and/or pose data, noise in data, or the like. For example, due to such lag time and/or noise, errors may exist in one or more geometry updates, phase encoding gradient updates, read encoding gradient updates, and/or calculation of a correction gradient, because all such calculations are based in part on the tracked pose and/or orientation data. Because the true pose and/or orientation data are available after data acquisition or a scan is complete, such discrepancies due to lag time or noise can be resolved. Further, any such residual errors that are corrected by the correction module 330 can further be stored in a database 332 of the main computing system 300.
[0091] The main computing system 300 can further comprise an image construction module 322. The image construction module 322 can be configured to construct and/or reconstruct an image based on the one or more signals emitted from the subject 308. In some embodiments, the image construction module 322 can further be configured to construct and/or reconstruct an image based in part on data that is processed by the magnetic resonance imaging sequence module 324, the geometry update module 316, phase encoding update module 318, read encoding gradient update module 320, correction gradient calculation module 326, and/or the correction module 330.
[0092] An image that is constructed and/or reconstructed by the image construction module 322 can further be transmitted over a computer network or other connection to one or more displays for outputting a constructed image 334. A user and/or medical professional can view the constructed image via the display for outputting the constructed image 334.
Intra-Scan Motion Correction - Method Overview
[0093] Systems, methods, and devices for intra-scan motion correction compensate not only from one line or acquisition step to the next, but also within each acquisition step or line in k-space.
[0094] Figure 4 is a time frame diagram that illustrates the time frame of one or more methods for an intra-scan motion correction. In some embodiments, a method for an intra-scan motion correction can comprise one or more blocks, including but not limited to an update geometry parameters block, an update phase and/or read encoding gradient(s) block, an apply correction gradient block, and/or an error correction block or any sub-blocks thereof. Additionally, a method for intra-scan motion correction can comprise a phase correction block. Further, a method for intra-scan motion correction can comprise any selective combination of these blocks and/or more specific blocks thereof.
[0095] In some embodiments, the update geometry parameters block, update phase and/or read encoding gradient(s) block, apply correction gradient block, and apply phase correction block, can be applied on a magnetic resonance scanner in near real-time. In certain embodiments, the error correction block can be applied after data acquisition during image reconstruction. However, other implementations are possible as well.
[0096] In some embodiments, an update geometry parameters block can comprise updating a prospective slice and/or geometry 402. The prospective slice and/or geometry update can occur immediately before one or more radiofrequency pulses. For example, a prospective slice and/or geometry update can occur prior to and/or immediately prior to excitation via an initial radiofrequency pulse. The prospective slice and/or geometry update can also occur prior to and/or immediately prior to an optional initial magnetic gradient field. In addition, a prospective slice and/or geometry update can occur prior to and/or immediately prior to any additional radiofrequency pulses and/or optional magnetic gradient fields. In certain embodiments, there can be one or more additional radiofrequency pulses and/or optional magnetic gradient fields. In other embodiments, there are no additional radiofrequency pulses and/or optional magnetic gradient fields.
[0097] In some embodiments an update phase and/or read encoding gradients block can comprise prospectively updating the orientation or pose of a phase encoding gradient and/or a frequency (read) encoding gradient. The prospective phase encoding gradient update can occur at any time between excitation and data acquisition 410. For example in some embodiments, a prospective phase encoding gradient update 404 can occur immediately after excitation and/or an optional magnetic gradient field. In certain embodiments, a prospective phase encoding gradient update 404 can occur at a time after excitation and/or optional magnetic gradient field. In certain embodiments, a prospective phase encoding gradient update 404 can occur in connection with an additional radiofrequency pulse and/or optional magnetic gradient field. In certain embodiments, a prospective phase encoding gradient 404 can occur concurrently with and/or in conjunction with a data acquisition process 410.
[0098] In some embodiments, a prospective frequency encoding gradient update 406 can begin prior to and/or immediately prior to a data acquisition process 410. In certain embodiments, a prospective frequency encoding gradient update 406 can occur concurrently with and in conjunction with a data acquisition process 410. In certain embodiments, a prospective frequency encoding gradient update 406 can end immediately prior to the end of a data acquisition process 410.
[0099] An apply correction gradient block can comprise applying a brief additional gradient 408 to the subject to correct for a first gradient moment as discussed above. In certain embodiments the correction gradient 408 can be applied after excitation and/or optional magnetic gradient fields and any additional radiofrequency pulses and/or optional magnetic gradient fields. In certain embodiments, the correction gradient 408 can be applied to the subject immediately prior to data acquisition 410. In certain embodiments, the correction gradient 408 can be applied to the subject concurrently with any other magnetic field gradient.
[0100] Further, an apply phase correction block can comprise setting the phase of the MR detector or receiver, or the phase of the data acquisition 410 device to correct for zero-order phase errors 409 as determined by Equation 2. In certain embodiments, the phase correction block can be applied to the subject immediately prior to or concurrent with data acquisition 410.
[0101] In some embodiments an error correction block can comprise correcting any residual error 412 after data acquisition. In some embodiments, residual errors in one or more geometry parameters, phase, and/or gradient moments are corrected in the error correction block. Such errors can be present after applying or without applying one or more geometry updates, phase encoding updates, read encoding gradient updates, phase corrections and/or application of an additional correction gradient.
[0102] In certain embodiments, residual errors can remain after processing the magnetic resonance data, with or without the update geometry parameters block, update phase and/or read encoding gradients block, and/or apply correction gradient block. In certain embodiments the error correction 412 can occur after and/or immediately after data acquisition 410.
[0103] In some embodiments after the error correction block the system is configured to construct and/or reconstruct an image of the subject 414. In certain embodiments the system can be configured to reconstruct the image based on the magnetic resonance data as inputted into k-space. In some embodiments, the system is configured to reconstruct an image further based on prospectively updated slices, phase encoding gradient updates, frequency encoding gradient updates, application of a correction gradient, and/or error correction.
Update Geometry Parameters Block
[0104] In some embodiments, one or more geometry parameters are updated prospectively. For example, one or more geometry parameters can be updated after excitation but before data acquisition. By prospectively updating one or more geometric parameters rather than after data acquisition, data processing time can be saved and a more isotropic, rectangular coverage of k-space can be obtained. If the one or more geometric parameters are updated only retrospectively after data acquisition, certain areas in k-space can be denser than others, possibly resulting in image artifacts and/or more complex reconstruction. Further, if the one or more geometric parameters are updated only retrospectively after data acquisition, certain signals may be attenuated or lost, and cannot be recovered during image reconstruction.
[0105] Figure 5 illustrates a process flow of an example of embodiments of one or more methods of intra-scan motion correction during a magnetic resonance scan. In some embodiments, the update geometry parameters block can be applied alone or in conjunction with one or more of an update phase and/or read encoding gradient(s) block, apply correction gradient block, apply correction phase block, and/or error correction block or sub-blocks thereof.
[0106] In some embodiments, the orientation and/or pose of a subject is tracked via one or more motion detectors at block 502. Based on the tracked orientation and/or pose of the subject the system can be configured to prospectively update one or more geometric parameters and/or slice planes at block 504. The one or more geometric parameters can comprise one or more parameters discussed above, including but not limited to translation and rotation. As discussed, the prospective update of geometric parameters and/or slice planes 504 can occur prior to and/or immediately prior to excitation of the spin system by applying an initial radiofrequency pulse at block 506. Further, the excitation can occur in conjunction with an optional magnetic field gradient at block 506.
[0107] Subsequent prospective updates of geometric parameters and/or slice planes can occur at block 508. As discussed, any of one or more, if any, subsequent prospective updates of geometric parameters and/or slice planes 508 can occur prior to and/or immediately prior to applying additional radiofrequency pulses at block 510. The radiofrequency pulses can be slice-selective refocusing, and/or slice-selective saturation and/or inversion pulses among others. The additional radiofrequency pulses can also be applied in conjunction with, before, and/or after applying an optional magnetic field gradient at block 510.
[0108] By updating the geometry parameters and/or slice planes immediately prior to all radiofrequency pulses, a line-by-line correction of motion between successive excitations is possible. In other words, signals throughout the entire measurement can be aligned in position.
[0109] In some embodiments, the system can be configured to conduct data acquisition at block 512 based on the scanned magnetic resonance data.
Update Phase and/or Read Encoding Gradient(s Block
[0110] As discussed, motion of a subject during a magnetic resonance scan can also affect the orientation of phase/read encoding gradient, thereby resulting in motion artifacts. As such, in some embodiments, the orientations of phase and/or read encoding gradients are prospectively updated. By prospectively updating the orientation of phase and/or read encoding gradients rather than after data acquisition, data processing time can be saved and a more isotropic, rectangular grid in k-space can be obtained. In other words, a more homogeneous coverage in density in k-space is possible. If the phase and/or read encoding gradients are updated only retrospectively after data acquisition, certain areas in k- space can be denser than others, possibly resulting in more complex reconstruction and/or in image artifacts. Further, if the phase and/or read encoding gradients are updated only retrospectively after data acquisition, certain signals may be encoded incorrectly, and cannot be recovered during image reconstruction.
[0111] Figure 6 illustrates an example of an embodiment of an update phase and/or read encoding gradient(s) block of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan. In some embodiments, the update phase and/or read encoding gradient(s) block can be applied alone or in conjunction with one or more of an update geometry parameters block, apply correction gradient block, apply correction phase block , and/or error correction block or sub-blocks thereof. [0112] In some embodiments, at block 602, one or more motion detectors are configured to track the orientation and/or pose of the subject during a magnetic resonance scan. In some embodiments, the system can further be configured to apply excitation of the spin system at block 604 by applying a radiofrequency pulse. In certain embodiments excitation of the spin system can occur in conjunction with, before, and/or after applying an optional magnetic field gradient at block 604.
[0113] As discussed, the orientation of a phase encoding gradient can be updated at any time after excitation and/or in conjunction with data acquisition 614. Prospectively updating the orientation of read encoding gradient and/or phase encoding gradient can occur at one or more of the blocks depicted in Figure 6. Accordingly, in some embodiments, a phase encoding gradient can be prospectively updated at block 606 after excitation of the spin system at block 604. However, a prospective update of the phase encoding gradient need not occur at this time. Alternatively, a prospective update of the phase encoding gradient can occur at block 610 after applying one or more additional radiofrequency pulses at block 608. As discussed, any additional radiofrequency pulses can be applied at block 608 in conjunction with, before, and/or after applying an optional magnetic field gradient.
[0114] Further, a prospective update of the orientation of read encoding gradient can occur at block 612 immediately prior to data acquisition at block 614. In certain embodiments, the read encoding gradient can be updated at block 616 in conjunction with data acquisition at block 614. In certain embodiments, the read encoding gradient can be updated immediately prior to data acquisition 614 at block 612 and repeatedly in conjunction with data acquisition 614 at block 616. Also, the phase encoding gradient can also be updated in conjunction with data acquisition 614 at block 618.
Apply Correction Gradient Block
[0115] If a subject of a magnetic resonance scan remains completely still and does not move during the scan, the first gradient moment over the scan should ideally equal zero for a balanced magnetic resonance sequence. However, if a subject of a magnetic resonance scan moves even slightly, the first gradient moment after completion of the scan does not equal zero. The transverse magnetization generated by the excitation pulse is affected by motion that occurs in the presence of gradients. Such motion affects the phase of the magnetization and thus the first order gradient moment depending on the direction and velocity of motion, and the direction and sequence of the gradients applied.
[0116] As noted, motion affects the gradient moment / position of "lines" in k- space. If the movement is known or predicted, then the gradient moment effects can be calculated as per Equation 1. Gradient moment alterations can be compensated for by the application of additional brief gradient pulses prior to signal detection. Importantly, this type of motion compensation with correction gradients is applicable for rotations.
[0117] Of note, many preparation RF pulses act on longitudinal magnetization to modify the image contrast. Because longitudinal magnetization is not affected by gradients, it can be unnecessary to apply correction compensation gradients in this instance. In other words, simply correcting the geometry via one or more sub-blocks of the update geometry parameters block may be sufficient.
[0118] Figure 7 illustrates an example of an embodiment of an apply correction gradient block of an embodiment of a method of intra- scan motion correction during a magnetic resonance scan. In some embodiments, the apply correction gradient block can be applied alone or in conjunction with one or more of an update geometry parameters block, update phase and/or read encoding gradient(s) block, apply correction phase block, and/or error correction block or sub-blocks thereof.
[0119] As illustrated in Figure 7, the system can be configured to track the orientation and/or pose of a subject during the scan via one or more motion detectors at block 702. In some embodiments, the spin system is excited by applying an initial radiofrequency pulse at block 704. Further, as discussed, in certain embodiments, the excitation can be applied in conjunction with one or more optional magnetic field gradients at block 704. In other embodiments, the system can be configured to apply additional magnetic field gradients. Such magnetic field gradients can comprise, for example, diffusion weighting gradients, flow encoding gradients, elasticity encoding gradients, gradients to eliminate unwanted spin coherences called spoiler or crusher gradients, gradients to prewind or rewind gradient moments, and/or other gradients. Additionally, one or more additional radiofrequency pulses can be applied to the subject at block 706. These one or more additional radiofrequency pulses can also be applied in conjunction with, before, and/or after applying one or more optional magnetic field gradients at block 706. Apply Phase Correction Block
[0120] Further, if a subject of a magnetic resonance scan moves even slightly, the phase of the signal is altered. The transverse magnetization generated by the excitation pulse is affected by motion that occurs in the presence of gradients. Such motion affects the phase of the magnetization depending on the direction and velocity of motion, and the direction and sequence of the gradients applied.
[0121] Motion affects both the phase of the signals acquired, as well as the gradient moment / position of "lines" in k-space. If the movement is known or predicted, then the phase effect can be calculated as per Equation 2. Phase alterations as per equation 2 may be compensated for by acquiring data at the correct reference-phase.
[0122] Accordingly, in some embodiments, a method of intra-scan motion correction comprises an apply correction phase block. Figure 7A illustrates an example of an embodiment of an apply correction phase block of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan. In some embodiments, the apply phase gradient block can be applied alone or in conjunction with one or more of an update geometry parameters block, update phase and/or read encoding gradient(s) block, apply gradient correction block, and/or error correction block or sub-blocks thereof.
[0123] In some embodiments the apply correction phase block can comprise calculating the correction phase at block 720. More specifically, Equation 2 and the tracked pose can be utilized to calculate the correction phase. The calculated correction phase can be applied to compensate for any or all phase effects at block 722. Further, the system can be configured to conduct data acquisition at block 724 after applying the correction gradient block in some embodiments.
Error Correction Block
[0124] In some situations, error can be present after data acquisition. For example, in some embodiments where the geometry, phase, and/or read encoding gradients are not updated prospectively or if a correction gradient is not applied, phase/gradient error and orientation error can be present in the data acquired. In certain embodiments, even after applying one or more of an update geometry parameters block, update phase and/or read encoding gradient(s) block, apply correction phase block, and/or apply correction gradient block, residual error in the phase/gradient and/or orientation can still be present. For example, the prospective update blocks are based on packets of orientation and/or pose data that are transmitted periodically from one or motion detectors to the computing system. However, there is an inherent lag time involved in the transmittal and processing of this data. Accordingly, one or more errors can still remain after prospective update blocks. As such, in some embodiments, an error correction block is applied to retrospectively correct for any remaining error.
[0125] Figure 8 is a process flow diagram illustrating an error correction block. In some embodiments, the error correction block can be applied alone or in conjunction with one or more of an update geometry parameters block, update phase and/or read encoding gradient(s) block, apply correction phase block, and/or apply correction gradient block or sub-blocks thereof.
[0126] In some embodiments, a system can be configured to track the orientation and/or pose of a subject during a magnetic resonance imaging scan via one or more motion detectors at block 802. In certain embodiments, the spin system can be excited by applying an initial radiofrequency pulse at block 804. The excitation, in certain embodiments, can be applied in conjunction with applying an optional magnetic field gradient at block 804. In some embodiments the system can be configured to apply one or more additional radiofrequency pulses at block 806. The one or more additional radiofrequency pulses can also be applied in conjunction with, before, and/or after one or more magnetic field gradients. The magnetic resonance scan data can be collected at block 808 by the system in some embodiments.
[0127] Any residual errors that are present after data acquisition 808 can be determined by the system and/or corrected during an error correction block. For example, any residual errors in one or more geometry parameters and/or phase or gradient moment that are present after applying or without applying one or more geometry updates, phase encoding updates, read encoding gradient updates, and/or application of an additional correction gradient can be corrected.
[0128] In certain embodiment, the system can be configured to determine discrepancies between predicted motion, from the orientation and/or pose data that was collected and transmitted periodically to the system at block 802, and the actual motion data at block 810. The actual motion data, in certain embodiments, can only be determined after the data acquisition process is complete.
[0129] As discussed above, errors in the predicted motion from the orientation and/or pose data that is periodically detected and sent to the system at block 802 can comprise one or more errors due to the inherent lag time and/or noise. Because of such potential errors in the predicted motion data, there can also be some residual errors in orientation and/or pose or phase/gradient even after applying one or more of an update geometry parameters block, update phase and/or read encoding gradient(s) block, apply correction gradient block, apply correction phase block, and/or sub-blocks thereof. Such residual errors can be corrected during the error correction block based on the determined discrepancies between the predicted motion and actual motion.
[0130] Further, small errors in the orientation of phase and read-encoding gradients can also be corrected during reconstruction, for instance, by interpolating the originally acquired raw data to a rectilinear raw data grid prior to Fourier transformation.
[0131] In some embodiments, the system can be configured to reconstruct an image based on the magnetic resonance scan, orientation and/or pose update, phase encoding gradient update, read gradient update, application of correction gradient, apply correction phase block, and/or any errors corrected during the error correction block at block 814.
Motion Effects - Examples
[0132] Figure 9 is a schematic diagram illustrating the effects of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan. The illustrated embodiment in Figure 9 comprises prospectively updating one or more geometry parameters, prospectively updating phase and/or read gradient(s), and applying a correction gradient.
[0133] As discussed above, in some embodiments, one or more slice updates or geometric updates are applied prior to and/or immediately prior to one or more radiofrequency pulses, including but not limited to excitation of the spin system. RF1 through RF3 correspond to one or more radiofrequency pulses. As illustrated, a slice update can occur immediately prior to application of radiofrequency pulse RF1. Further, another slice update can occur immediately prior to another radiofrequency pulse RF2. Additionally, another slice update can occur immediately prior to applying another radiofrequency pulse RF3.
[0134] PI through P7 correspond to individual periodic packets of orientation and/or pose data that is detected by one or more motion detectors and transmitted to the magnetic resonance system in some embodiments. As illustrated, one or more slice updates can be applied by the system using the orientation and/or pose data packet that was transmitted to the system immediately prior to one or more slice updates and/or geometric updates. For example, a first slice update can be applied based on data packet PI. Further, another slice update can be applied based on the orientation and/or pose data packet P2. Additionally, another slice update can occur using the orientation and/or pose data packet P6.
[0135] In contrast to some embodiments where motion of a subject between excitation, for example RF1, and data acquisition, AQ, is ignored as negligible, the depicted embodiment prospectively updates geometric parameters within a single magnetic resonance scanning step to obtain clearer images. The second horizontal line denoted SL corresponds to slice gradients and updates. As illustrated in Figure 9, the one or more slice updates are applied immediately prior to one or more radiofrequency pulses using an orientation and/or pose data packet that was received immediately prior to the slice update.
[0136] The third horizontal line denoted PH corresponds to phase encoding direction. As illustrated in Figure 9, the phase encoding gradient in some embodiments is updated immediately prior to data acquisition, which is labeled AQ. In some embodiments, the data acquisition can last for anywhere from about one milliseconds to about 100 milliseconds or longer.
[0137] The fourth horizontal line denoted RO corresponds to the readout direction. As illustrated in Figure 9, in some embodiments the read encoding update is applied immediately prior to or concurrently with data acquisition. In some embodiments, read encoding update is not required. Rather, only phase encoding update and/or geometry update is applied.
[0138] Gl through G4 in the PH horizontal line correspond to additional magnetic field gradients used to encode additional information, such as microscopic diffusion of molecules, or to eliminate unwanted signals, or for other purposes. As discussed above, if a subject does not move and remains completely still during a magnetic resonance scan, there is no gradient moment build-up. In other words, the sum of the areas of G1-G4 should equal zero. However, if the subject moves during a magnetic resonance scan, the interaction of gradients Gl through G4 with the moving subject causes the gradient moment build-up to not equal zero. This gradient moment build-up can cause additional motion artifacts in the scanned image.
[0139] Accordingly, in some embodiments, the system is configured to apply an additional brief gradient or a correction gradient to reverse the effects of the total gradient moment. In some embodiments, the correction gradient is simply the inverse of the gradient moment build-up. In the depicted embodiment, a "blip" or a correction gradient moment is calculated prior to or immediately prior to data acquisition. As illustrated, in order to calculate the gradient moment build-up, which is the integral of the gradient sequence multiplied by the rotation matrix during the scan, orientation and/or pose data packets from the entire scan duration can be used. For example, in the depicted embodiment, P1-P7 can be used in conjunction with the gradient sequence to calculate the gradient moment build-up.
[0140] However, as discussed, lag time and/or noise may be present in the orientation and/or pose data packets. For example, it requires time for data packet P5 to be transmitted from one or more motion detectors to the computer system and to be processed. As a result, such lag time and/or noise in orientation and/or pose data leads to possible errors in the prospective updates to one or more geometry parameters, phase/gradient, and/or calculation of a correction gradient.
[0141] However, after data acquisition, in some embodiments, the one or more motion detectors can be configured to continue to collect orientation and/or pose data, for example P8 and/or P9. With such continued data, the lag time can be accounted for. For example, each data packet can be shifted in time by a certain amount in order to account for the lag time. By shifting the time of orientation and/or pose data, the system can obtain true orientation and/or pose data and determine and/or correct any errors remaining after data acquisition.
[0142] Figure 10 is another schematic diagram illustrating the effects of an embodiment of a method of intra-scan motion correction during a magnetic resonance scan. In Figure 10, the first horizontal line RF illustrates the radiofrequency sequences. GSL, GPE, and GRO represent slice gradient, phase encoding gradient, and readout gradient respectively. [0143] The echo time (TE) corresponds to the time between the center or excitation and the center of data acquisition. Similar to Figure 9, a slice update is conducted by the system immediately prior to excitation. Further, a phase encoding gradient update is conducted by the system between excitation and data acquisition. Additionally, a correction gradient is applied by the system to the subject before data acquisition. The correction gradient in Figure 10 is illustrated by the pulses located within the oval. Moreover, a read encoding gradient update can be conducted by the system in conjunction with data acquisition. For example, a read encoding gradient update process can begin immediately prior to data acquisition and continue to be conducted throughout the data acquisition process.
[0144] Further, in Figure 10, another slice update is applied immediately before excitation of a second magnetic resonance scan. Repetition time (TR) refers to the time between the excitation of a first scan and a second scan.
[0145] As discussed, many embodiments of non-intrascan motion correction systems update scan parameters only once prior to each "excitation" radiofrequency (RF) pulse, which is typically every 100ms or less frequently. Further, some of such embodiments only correct slice locations. Since the subject position and orientation is assumed to be static between a given "excitation" and "readout", such a scheme can work well for relatively slow movements, on the order of a few millimeters / second. However, more rapid movements require dynamic updates of sequence parameters (for instance every few milliseconds) between excitation and acquisition, i.e. within each line of k-space. Of note, some tracking techniques, such as optical techniques, can allow very rapid and accurate tracking, from 100 to up to 1000 times per second.
[0146] Consequently, updating scan parameters "intra-scan" as described herein can allow compensation of even the most rapid movements, up to 10s or 100s of mm / second or even higher. Therefore, rapidly repeated motion correction with "intra-scan" updates as described herein makes it possible to perform high-quality MR scans in very sick or confused subjects or children, without the need for anesthesia.
[0147] Importantly, the concepts described herein can generally be applied to any imaging or spectroscopy sequence and therefore can constitute a universal method to compensate the effects of subject motion in any MR scan. For some spectroscopy scans, data may not be acquired in k-space (i.e. without use of readout gradients); however, the methods disclosed can be used to eliminate phase errors and / or imbalances in gradient moments due to motion, which otherwise result in signal reduction and spectral distortions due to non coherent averaging of signals. Likewise, some imaging techniques use non-rectangular sampling in k-space, but the methods described can easily be adapted to such sampling schemes.
Computing System
[0148] In some embodiments, the computer clients and/or servers described above take the form of a computing system 1100 illustrated in Figure 11, which is a block diagram of one embodiment of a computing system that is in communication with one or more computing systems 1110 and/or one or more data sources 1120 via one or more networks 1116. The computing system 1100 may be used to implement one or more of the systems and methods described herein. In addition, in one embodiment, the computing system 1100 may be configured to apply one or more of the intra-scan motion correction techniques described herein. While Figure 11 illustrates one embodiment of a computing system 1100, it is recognized that the functionality provided for in the components and modules of computing system 1100 may be combined into fewer components and modules or further separated into additional components and modules.
Motion Correction Module
[0149] In one embodiment, the system 1100 comprises a motion correction module 1106 that carries out the functions described herein with reference to repeatedly correcting motion effects during a scan, including any one of the intra-scan motion correction techniques described above. The motion correction module 1106 may be executed on the computing system 1100 by a central processing unit 1102 discussed further below.
[0150] In general, the word "module," as used herein, refers to logic embodied in hardware or firmware, or to a collection of software instructions, possibly having entry and exit points, written in a programming language, such as, for example, COBOL, CICS, Java, Lua, C or C++. A software module may be compiled and linked into an executable program, installed in a dynamic link library, or may be written in an interpreted programming language such as, for example, BASIC, Perl, or Python. It will be appreciated that software modules may be callable from other modules or from themselves, and/or may be invoked in response to detected events or interrupts. Software instructions may be embedded in firmware, such as an EPROM. It will be further appreciated that hardware modules may be comprised of connected logic units, such as gates and flip-flops, and/or may be comprised of programmable units, such as programmable gate arrays or processors. The modules described herein are preferably implemented as software modules, but may be represented in hardware or firmware. Generally, the modules described herein refer to logical modules that may be combined with other modules or divided into sub-modules despite their physical organization or storage.
Computing System Components
[0151] In one embodiment, the computing system 1100 also comprises a mainframe computer suitable for controlling and/or communicating with large databases, performing high volume transaction processing, and generating reports from large databases. The computing system 1100 also comprises a central processing unit ("CPU") 1102, which may comprise a conventional microprocessor. The computing system 1100 further comprises a memory 1104, such as random access memory ("RAM") for temporary storage of information and/or a read only memory ("ROM") for permanent storage of information, and a mass storage device 1108, such as a hard drive, diskette, or optical media storage device. Typically, the modules of the computing system 1100 are connected to the computer using a standards based bus system. In different embodiments, the standards based bus system could be Peripheral Component Interconnect (PCI), MicroChannel, SCSI, Industrial Standard Architecture (ISA) and Extended ISA (EISA) architectures, for example.
[0152] The computing system 1100 comprises one or more commonly available input/output (I/O) devices and interfaces 1112, such as a keyboard, mouse, touchpad, and printer. In one embodiment, the I/O devices and interfaces 1112 comprise one or more display devices, such as a monitor, that allows the visual presentation of data to a user. More particularly, a display device provides for the presentation of GUIs, application software data, and multimedia presentations, for example. In the embodiment of Figure 11, the I/O devices and interfaces 1112 also provide a communications interface to various external devices. The computing system 1100 may also comprise one or more multimedia devices 1110, such as speakers, video cards, graphics accelerators, and microphones, for example. Computing System Device/Operating System
[0153] The computing system 1100 may run on a variety of computing devices, such as, for example, a server, a Windows server, an Structure Query Language server, a Unix server, a personal computer, a mainframe computer, a laptop computer, a cell phone, a personal digital assistant, a kiosk, an audio player, and so forth. The computing system 1100 is generally controlled and coordinated by operating system software, such as z/OS, Windows 95, Windows 98, Windows NT, Windows 2000, Windows XP, Windows Vista, Windows 7, Linux, BSD, SunOS, Solaris, or other compatible operating systems. In Macintosh systems, the operating system may be any available operating system, such as MAC OS X. In other embodiments, the computing system 5800 may be controlled by a proprietary operating system. Conventional operating systems control and schedule computer processes for execution, perform memory management, provide file system, networking, and I/O services, and provide a user interface, such as a graphical user interface ("GUI"), among other things.
Network
[0154] In the embodiment of Figure 11, the computing system 1100 is coupled to a network 1116, such as a LAN, WAN, or the Internet, for example, via a wired, wireless, or combination of wired and wireless, communication link 1114. The network 1116 communicates with various computing devices and/or other electronic devices via wired or wireless communication links. In the embodiment of Figure 11, the network 1116 is communicating with one or more computing systems 1118 and/or one or more data sources 1120.
[0155] Access to the image construction module 1106 of the computer system 1100 by computing systems 1118 and/or by data sources 1120 may be through a web-enabled user access point such as the computing systems' 1118 or data source's 1120 personal computer, cellular phone, laptop, or other device capable of connecting to the network 1116. Such a device may have a browser module is implemented as a module that uses text, graphics, audio, video, and other media to present data and to allow interaction with data via the network 1116.
[0156] The browser module may be implemented as a combination of an all points addressable display such as a cathode-ray tube (CRT), a liquid crystal display (LCD), a plasma display, or other types and/or combinations of displays. In addition, the browser module may be implemented to communicate with input devices 1112 and may also comprise software with the appropriate interfaces which allow a user to access data through the use of stylized screen elements such as, for example, menus, windows, dialog boxes, toolbars, and controls (for example, radio buttons, check boxes, sliding scales, and so forth). Furthermore, the browser module may communicate with a set of input and output devices to receive signals from the user.
[0157] The input device(s) may comprise a keyboard, roller ball, pen and stylus, mouse, trackball, voice recognition system, or pre-designated switches or buttons. The output device(s) may comprise a speaker, a display screen, a printer, or a voice synthesizer. In addition a touch screen may act as a hybrid input/output device. In another embodiment, a user may interact with the system more directly such as through a system terminal connected to the score generator without communications over the Internet, a WAN, or LAN, or similar network.
[0158] In some embodiments, the system 1100 may comprise a physical or logical connection established between a remote microprocessor and a mainframe host computer for the express purpose of uploading, downloading, or viewing interactive data and databases on-line in real time. The remote microprocessor may be operated by an entity operating the computer system 1100, including the client server systems or the main server system, an/or may be operated by one or more of the data sources 1120 and/or one or more of the computing systems. In some embodiments, terminal emulation software may be used on the microprocessor for participating in the micro -mainframe link.
[0159] In some embodiments, computing systems 1118 who are internal to an entity operating the computer system 1100 may access the image construction module 1106 internally as an application or process run by the CPU 1102.
User Access Point
[0160] In an embodiment, a user access point or user interface 1112 comprises a personal computer, a laptop computer, a cellular phone, a GPS system, a Blackberry® device, a portable computing device, a server, a computer workstation, a local area network of individual computers, an interactive kiosk, a personal digital assistant, an interactive wireless communications device, a handheld computer, an embedded computing device, or the like.
Other Systems
[0161] In addition to the systems that are illustrated in Figure 11, the network 1116 may communicate with other data sources or other computing devices. The computing system 1100 may also comprise one or more internal and/or external data sources. In some embodiments, one or more of the data repositories and the data sources may be implemented using a relational database, such as DB2, Sybase, Oracle, CodeBase and Microsoft® SQL Server as well as other types of databases such as, for example, a signal database, object- oriented database, and/or a record-based database.
[0162] Conditional language, such as, among others, "can," "could," "might," or "may," unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain embodiments include, while other embodiments do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without user input or prompting, whether these features, elements and/or steps are included or are to be performed in any particular embodiment. The headings used herein are for the convenience of the reader only and are not meant to limit the scope of the inventions or claims.
[0163] Although this invention has been disclosed in the context of certain preferred embodiments and examples, it will be understood by those skilled in the art that the present invention extends beyond the specifically disclosed embodiments to other alternative embodiments and/or uses of the invention and obvious modifications and equivalents thereof. Additionally, the skilled artisan will recognize that any of the above-described methods can be carried out using any appropriate apparatus. Further, the disclosure herein of any particular feature, aspect, method, property, characteristic, quality, attribute, element, or the like in connection with an embodiment can be used in all other embodiments set forth herein. For all of the embodiments described herein the steps of the methods need not be performed sequentially. Thus, it is intended that the scope of the present invention herein disclosed should not be limited by the particular disclosed embodiments described above.

Claims

WHAT IS CLAIMED IS:
1. A magnetic resonance system configured to correct intra-scan motion during a magnetic resonance scan, the system comprising:
a magnetic resonance scanner configured to generate a magnetic field gradient and a radiofrequency signal for the magnetic resonance scan;
a motion tracking system configured to track one or more pose parameters of a subject and transmit pose data corresponding to the tracked one or more pose parameters at a given time to the magnetic resonance scanner;
an electronic memory storage configured to store modules; and a computer processor configured to execute the modules comprising at least: a correction gradient calculation module configured to calculate a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the transmitted pose data and a gradient sequence used for the magnetic resonance scan;
the magnetic resonance scanner further configured to apply the correction gradient to the subject prior to detecting signals emitted from the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan; and
the magnetic resonance scanner further configured to detect the signals emitted from the subject for data acquisition.
2. The magnetic resonance system of Claim 1, further comprising an error correction module configured to compare the transmitted pose data to final pose data and eliminate one or more residual errors in the calculation of the moment of the correction gradient, wherein the final orientation data is available after data acquisition.
3. The magnetic resonance system of Claim 1, further comprising a geometry update module configured to update one or more geometric parameters based on the transmitted pose data to correct errors in the one or more geometric parameters due to movement of the subject.
4. The magnetic resonance system of Claim 3, wherein the geometry update module is configured to update the one or more geometric parameters prior to one or more radiofrequency pulses.
5. The magnetic resonance system of Claim 3, wherein the geometry update module is configured to update the one or more geometric parameters prior to each radiofrequency pulse.
6. The magnetic resonance system of Claim 3, further comprising an error correction module configured to compare the transmitted pose data to final pose data and eliminate one or more residual errors in the one or more geometric parameters, wherein the final orientation data is available after data acquisition.
7. The magnetic resonance system of Claim 1, further comprising a phase encoding update module configured to update one or more phase encoding gradients based on the transmitted pose data.
8. The magnetic resonance system of Claim 7, further comprising an error correction module configured to compare the transmitted pose data to final pose data and eliminate one or more residual errors in the updates to the one or more phase encoding gradients, wherein the final orientation data is available after data acquisition.
9. The magnetic resonance system of Claim 7, wherein the phase encoding update module is configured to update the one or more phase encoding gradients after excitation and prior to data acquisition by the magnetic resonance scanner.
10. The magnetic resonance system of Claim 7, wherein the phase encoding update module is configured to update the one or more phase encoding gradients concurrently with data acquisition by the magnetic resonance scanner.
11. The magnetic resonance system of Claim 1, further comprising a read encoding gradient update module configured to update one or more read encoding gradients based on the transmitted orientation data.
12. The magnetic resonance system of Claim 11, further comprising an error correction module configured to compare the transmitted pose data to final pose data and eliminate one or more residual errors in the updates to the one or more read encoding gradients, wherein the final orientation data is available after data acquisition.
13. The magnetic resonance system of Claim 11, wherein the read encoding update module is configured to update the one or more read encoding gradients after excitation and prior to data acquisition by the magnetic resonance scanner.
14. The magnetic resonance system of Claim 11, wherein the read encoding gradient update module is configured to update the one or more read encoding gradients concurrently with data acquisition by the magnetic resonance scanner.
15. The magnetic resonance system of Claim 1, wherein the moment of the correction gradient is calculated to reverse a first gradient moment, wherein the first gradient moment is calculated from the transmitted pose data according to:
T
M = R-1 (t) - G(t) - dt
0 wherein R(t) is a rotation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
16. The magnetic resonance system of Claim 1, further comprising a phase correction module configured to correct errors in one or more phases.
17. The magnetic resonance system of Claim 16, wherein the phase correction module is configured to correct errors in the one or more phases based on:
Figure imgf000048_0001
wherein X(t) is a translation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
18. The magnetic resonance system of Claim 1, wherein the one or more of transmitted pose data used to calculate the moment of the correction gradient is shifted in time to correct for one or more prediction errors related to the transmitted pose data.
19. The magnetic resonance system of Claim 18, wherein the one or more prediction errors comprise lag time, noise, and changes in motion pattern.
20. The magnetic resonance system of Claim 1, wherein the motion tracking system comprises a Moire Phase Tracking system.
21. The magnetic resonance system of Claim 1, wherein the motion tracking system comprises a stereovision tracking system.
22. The magnetic resonance system of Claim 1, wherein the correction gradient is an additional magnetic gradient to be applied to the subject for a period of time.
23. The magnetic resonance system of Claim 1, wherein the correction gradient is applied in conjunction with another gradient.
24. The magnetic resonance system of Claim 1, wherein the system is capable of correcting one or more errors due to movement of the subject occurring at greater than 10 mm per second.
25. An intra- scan motion correction system, the system comprising:
an electronic memory storage configured to store modules; and a computer processor configured to execute the modules comprising at least: a motion tracking module configured to receive pose data of a subject from one or more motion tracking systems during a magnetic resonance scan of the subject; and
a correction gradient calculation module configured to calculate a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan.
26. The system of Claim 25, wherein the system is connected to a magnetic resonance system via a computer network.
27. The system of Claim 26, wherein the magnetic resonance system is configured to apply the correction gradient on the subject.
28. The system of Claim 25, wherein the correction gradient is an additional magnetic gradient to be applied to the subject for a period of time.
29. The system of Claim 25, wherein the correction gradient is applied in conjunction with another gradient.
30. The system of Claim 25, further comprising a geometry update module configured to update one or more geometric parameters based on the received pose data to correct errors in the one or more geometric parameters due to movement of the subject.
31. The system of Claim 25, further comprising a phase encoding update module configured to update one or more phase encoding gradients based on the received pose data.
32. The system of Claim 25, further comprising a read encoding gradient update module configured to update one or more read encoding gradients based on the received pose data.
33. The system of Claim 25, further comprising an error correction module configured to compare the received pose data to final pose data and eliminate one or more residual errors based on the comparison, wherein the final pose data is available after the magnetic resonance scan.
34. The system of Claim 33, wherein the one or more residual errors comprise errors in geometric orientation and signal phase.
35. The system of Claim 25, wherein the moment of the correction gradient is calculated to reverse a first gradient moment, wherein the first gradient moment is calculated from the received pose data according to:
Figure imgf000050_0001
0 wherein R(t) is a rotation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
36. The system of Claim 25, further comprising a phase correction module configured to correct errors in one or more phases.
37. The system of Claim 36, wherein the phase correction module is configured to correct errors in the one or more phases based on:
Figure imgf000050_0002
0
wherein X(t) is a translation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
38. The system of Claim 25, wherein the received pose data used to calculate the moment of the correction gradient is shifted in time to correct for one or more prediction errors related to the received pose data.
39. The system of Claim 25, wherein the system is capable of correcting one or more errors due to movement of the subject occurring at greater than 10 mm per second.
40. An intra-scan motion correction system, the system comprising:
an electronic memory storage configured to store modules; and a computer processor configured to execute the modules comprising at least: a motion tracking module configured to receive pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and
an error correction module configured to calculate a gradient moment based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the calculated gradient moment, and wherein the one or more errors in the gradient moment are corrected during reconstruction.
41. The system of Claim 40, wherein the system is connected to a magnetic resonance system via a computer network.
42. The system of Claim 40, further comprising a geometry update module configured to update one or more geometric parameters based on the received pose data to correct errors in the one or more geometric parameters due to movement of the subject.
43. The system of Claim 40, further comprising a phase encoding update module configured to prospectively update one or more phase encoding gradients based on the received pose data.
44. The system of Claim 40, further comprising a read encoding gradient update module configured to prospectively update one or more read encoding gradients based on the received pose data.
45. The system of Claim 40, further comprising a correction gradient calculation module configured to calculate a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in signal phase due to movement of the subject during the magnetic resonance scan.
46. The system of Claim 45, wherein the correction gradient is applied in conjunction with another gradient.
47. The system of Claim 45, wherein the moment of the correction gradient is calculated to reverse a first gradient moment, wherein the first gradient moment is calculated from the received pose data according to:
M = - G(t) - dt
Figure imgf000051_0001
wherein R(t) is a rotation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
48. The system of Claim 40, further comprising a phase correction module configured to correct errors in one or more phases.
49. The system of Claim 48, wherein the phase correction module is configured to correct errors in the one or more phases based on:
Figure imgf000052_0001
0
wherein X(t) is a translation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
50. The system of Claim 40, wherein the system is capable of correcting one or more errors due to movement of the subject occurring at greater than 10 mm per second.
51. An intra-scan motion correction system, the system comprising:
an electronic memory storage configured to store modules; and a computer processor configured to execute the modules comprising at least: a motion tracking module configured to receive pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and
an error correction module configured to calculate a phase based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the phase, and wherein the one or more errors in the phase are corrected during reconstruction.
52. The system of Claim 51, wherein the system is connected to a magnetic resonance system via a computer network.
53. The system of Claim 51, further comprising a geometry update module configured to update one or more geometric parameters based on the received pose data to correct errors in the one or more geometric parameters due to movement of the subject.
54. The system of Claim 51, further comprising a phase encoding update module configured to prospectively update one or more phase encoding gradients based on the received pose data.
55. The system of Claim 51, further comprising a read encoding gradient update module configured to prospectively update one or more read encoding gradients based on the received pose data.
56. The system of Claim 51, further comprising a correction gradient calculation module configured to calculate a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan.
57. The system of Claim 56, wherein the correction gradient is applied in conjunction with another gradient.
58. The system of Claim 56, wherein the moment of the correction gradient is calculated to reverse a first gradient moment, wherein the first gradient moment is calculated from the received pose data according to:
Figure imgf000053_0001
wherein R(t) is a rotation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
59. The system of Claim 51, further comprising a phase correction module configured to prospectively correct errors in one or more phases.
60. The system of Claim 59, wherein the phase correction module is configured to correct one or more errors in the phase based on:
Figure imgf000053_0002
0
wherein X(t) is a translation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
61. The system of Claim 51, wherein the error correction module is further configured to calculate a gradient moment based on the received pose data and the gradient sequence, wherein the error correction module is further configured to correct one or more errors in the calculated gradient moment, and wherein the one or more errors in the gradient moment are corrected during reconstruction.
62. The system of Claim 51, wherein the system is capable of correcting one or more errors due to movement of the subject occurring at greater than 10 mm per second.
63. A computer- implemented method of correcting for intra-scan motion during a magnetic resonance scan, the computer-implemented method comprising:
generating by a magnetic resonance scanner a magnetic field gradient and a radiofrequency signal for the magnetic resonance scan;
tracking by a motion tracking system one or more pose parameters of a subject and transmitting pose data corresponding to the tracked one or more pose parameters at a given time to the magnetic resonance scanner;
calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the transmitted pose data and a gradient sequence used for the magnetic resonance scan;
applying by the magnetic resonance scanner the correction gradient to the subject prior to detecting signals emitted from the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan; and
detecting by the magnetic resonance scanner the signals emitted from the subject for data acquisition,
wherein the computer comprises a computer processor and an electronic storage medium.
64. The computer-implemented method of Claim 63, further comprising comparing by an error correction module the transmitted pose data to final pose data and eliminate one or more residual errors in the calculation of the moment of the correction gradient, wherein the final orientation data is available after data acquisition.
65. The computer-implemented method of Claim 63, further comprising updating by a geometry update module one or more geometric parameters based on the transmitted pose data to correct errors in the one or more geometric parameters due to movement of the subject.
66. The computer- implemented method of Claim 65, wherein the geometry update module is configured to update the one or more geometric parameters prior to one or more radiofrequency pulses.
67. The computer- implemented method of Claim 65, wherein the geometry update module is configured to update the one or more geometric parameters prior to each radiofrequency pulse.
68. The computer-implemented method of Claim 65, further comprising comparing by an error correction module the transmitted pose data to final pose data and eliminating one or more residual errors in the one or more geometric parameters, wherein the final orientation data is available after data acquisition.
69. The computer-implemented method of Claim 63, further comprising updating by a phase encoding update module one or more phase encoding gradients based on the transmitted pose data.
70. The computer-implemented method of Claim 69, further comprising comparing by an error correction module the transmitted pose data to final pose data and eliminating one or more residual errors in the updates to the one or more phase encoding gradients, wherein the final orientation data is available after data acquisition.
71. The computer-implemented method of Claim 69, wherein the phase encoding update module is configured to update the one or more phase encoding gradients after excitation and prior to data acquisition by the magnetic resonance scanner.
72. The computer-implemented method of Claim 69, wherein the phase encoding update module is configured to update the one or more phase encoding gradients concurrently with data acquisition by the magnetic resonance scanner.
73. The computer-implemented method of Claim 63, further comprising updating by a read encoding gradient update module one or more read encoding gradients based on the transmitted orientation data.
74. The computer-implemented method of Claim 73, further comprising comparing by an error correction module the transmitted pose data to final pose data and eliminating one or more residual errors in the updates to the one or more read encoding gradients, wherein the final orientation data is available after data acquisition.
75. The computer-implemented method of Claim 73, wherein the read encoding update module is configured to update the one or more read encoding gradients after excitation and prior to data acquisition by the magnetic resonance scanner.
76. The computer-implemented method of Claim 73, wherein the read encoding gradient update module is configured to update the one or more read encoding gradients concurrently with data acquisition by the magnetic resonance scanner.
77. The computer-implemented method of Claim 63, wherein the moment of the correction gradient is calculated to reverse a first gradient moment, wherein the first gradient moment is calculated from the transmitted pose data according to:
Figure imgf000056_0001
wherein R(t) is a rotation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
78. The computer-implemented method of Claim 63, further comprising correcting by a phase correction module errors in one or more phases.
79. The computer-implemented method of Claim 78, wherein the phase correction module is configured to correct errors in the one or more phases based on:
Figure imgf000056_0002
wherein X(t) is a translation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
80. The computer-implemented method of Claim 63, wherein one or more transmitted pose data used to calculate the moment of the correction gradient is shifted in time to correct for one or more prediction errors related to the transmitted pose data.
81. The computer- implemented method of Claim 80, wherein the one or more prediction errors comprise lag time, noise, and changes in motion pattern.
82. The computer-implemented method of Claim 63, wherein the motion tracking system comprises a Moire Phase Tracking system.
83. The computer-implemented method of Claim 63, wherein the motion tracking system comprises a stereovision tracking system.
84. The computer-implemented method of Claim 63, wherein the correction gradient is an additional magnetic gradient to be applied to the subject for a period of time.
85. The computer-implemented method of Claim 63, wherein the correction gradient is applied in conjunction with another gradient.
86. The computer-implemented method of Claim 63, wherein the method is capable of correcting one or more errors due to movement of the subject occurring at greater than 10 mm per second.
87. A computer- implemented method of correcting for intra-scan motion during a magnetic resonance scan, the method comprising:
receiving by a motion tracking module pose data of a subject from one or more motion tracking systems during the magnetic resonance scan of the subject; and calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan,
wherein the computer comprises a computer processor and an electronic storage medium.
88. The computer-implemented method of Claim 87, wherein the motion tracking module and the correction gradient calculation module are connected to a magnetic resonance system via a computer network.
89. The computer-implemented method of Claim 88, wherein the magnetic resonance system is configured to apply the correction gradient on the subject.
90. The computer-implemented method of Claim 87, wherein the correction gradient is an additional magnetic gradient to be applied to the subject for a period of time.
91. The computer-implemented method of Claim 87, wherein the correction gradient is applied in conjunction with another gradient.
92. The computer-implemented method of Claim 87, further comprising updating by a geometry update module one or more geometric parameters based on the received pose data to correct errors in the one or more geometric parameters due to movement of the subject.
93. The computer-implemented method of Claim 87, further comprising updating by a phase encoding update module one or more phase encoding gradients based on the received pose data.
94. The computer-implemented method of Claim 87, further comprising updating by a read encoding gradient update module one or more read encoding gradients based on the received pose data.
95. The computer-implemented method of Claim 87, further comprising comparing by an error correction module the received pose data to final pose data and eliminating one or more residual errors based on the comparison, wherein the final pose data is available after the magnetic resonance scan.
96. The computer- implemented method of Claim 95, wherein the one or more residual errors comprise errors in geometric orientation and signal phase.
97. The computer- implemented method of Claim 87, wherein the moment of the correction gradient is calculated to reverse a first gradient moment, wherein the first gradient moment is calculated from the received pose data according to:
Figure imgf000058_0001
wherein R(t) is a rotation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
98. The computer-implemented method of Claim 87, further comprising correcting by a phase correction module errors in one or more phases.
99. The computer-implemented method of Claim 98, wherein the phase correction module is configured to correct errors in the one or more phases based on:
Figure imgf000058_0002
0
wherein X(t) is a translation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
100. The computer-implemented method of Claim 87, wherein the received pose data used to calculate the moment of the correction gradient is shifted in time to correct for one or more prediction errors related to the received pose data.
101. The computer- implemented method of Claim 87, wherein the method is capable of correcting one or more errors due to movement of the subject occurring at greater than 10 mm per second.
102. A computer-implemented method of correcting for intra-scan motion during a magnetic resonance scan, the method comprising:
receiving by a motion tracking module pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and
calculating by an error correction module a gradient moment based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the calculated gradient moment, and wherein the one or more errors in the gradient moment are corrected during reconstruction,
wherein the computer comprises a computer processor and an electronic storage medium.
103. The computer- implemented method of Claim 102, wherein the motion tracking module and the error correction module are connected to a magnetic resonance system via a computer network.
104. The computer-implemented method of Claim 102, further comprising updating by a geometry update module one or more geometric parameters based on the received pose data to correct errors in the one or more geometric parameters due to movement of the subject.
105. The computer- implemented method of Claim 102, further comprising prospectively updating by a phase encoding update module one or more phase encoding gradients based on the received pose data.
106. The computer- implemented method of Claim 102, further comprising prospectively updating by a read encoding gradient update module one or more read encoding gradients based on the received pose data.
107. The computer- implemented method of Claim 102, further comprising calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in signal phase due to movement of the subject during the magnetic resonance scan.
108. The computer- implemented method of Claim 107, wherein the correction gradient is applied in conjunction with another gradient.
109. The computer-implemented method of Claim 107, wherein the moment of the correction gradient is calculated to reverse a first gradient moment, wherein the first gradient moment is calculated from the received pose data according to:
T
M = R-1(t) - G(t) - dt
0 wherein R(t) is a rotation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
110. The computer-implemented method of Claim 102, further comprising correcting by a phase correction module errors in one or more phases.
111. The computer-implemented method of Claim 110, wherein the phase correction module is configured to correct errors in the one or more phases based on:
Figure imgf000060_0001
0
wherein X(t) is a translation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
112. The computer-implemented method of Claim 102, wherein the method is capable of correcting one or more errors due to movement of the subject occurring at greater than 10 mm per second.
113. A computer- implemented method of correcting for intra-scan motion during a magnetic resonance scan, the method comprising:
receiving by a motion tracking module pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and calculating by an error correction module a phase based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the phase, and wherein the one or more errors in the phase are corrected during reconstruction,
wherein the computer comprises a computer processor and an electronic storage medium.
114. The computer-implemented method of Claim 113, wherein the motion tracking module and the phase correction module are connected to a magnetic resonance system via a computer network.
115. The computer- implemented method of Claim 113, further comprising updating by a geometry update module one or more geometric parameters based on the received pose data to correct errors in the one or more geometric parameters due to movement of the subject.
116. The computer- implemented method of Claim 113, further comprising prospectively updating by a phase encoding update module one or more phase encoding gradients based on the received pose data.
117. The computer- implemented method of Claim 113, further comprising prospectively updating by a read encoding gradient update module one or more read encoding gradients based on the received pose data.
118. The computer- implemented method of Claim 113, further comprising calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan.
119. The computer- implemented method of Claim 118, wherein the correction gradient is applied in conjunction with another gradient.
120. The computer-implemented method of Claim 118, wherein the moment of the correction gradient is calculated to reverse a first gradient moment, wherein the first gradient moment is calculated from the received pose data according to:
T
M = R-1(t) - G(t) - dt wherein R(t) is a rotation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
121. The computer- implemented method of Claim 113, further comprising prospectively correcting by a phase correction module errors in the one or more phases
122. The computer-implemented method of Claim 121, wherein the phase correction module is configured to correct one or more errors in the phase based on:
Figure imgf000062_0001
0
wherein X(t) is a translation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
123. The computer- implemented method of Claim 113, further comprising calculating by the error correction module a gradient moment based on the received pose data and the gradient sequence, wherein the error correction module is further configured to correct one or more errors in the calculated gradient moment, and wherein the one or more errors in the gradient moment are corrected during reconstruction.
124. The computer-implemented method of Claim 113, wherein the method is capable of correcting one or more errors due to movement of the subject occurring at greater than 10 mm per second.
125. A computer-readable, non-transitory storage medium having a computer program stored thereon for causing a suitably programmed computer system to process by one or more computer processors computer-program code by performing a method to correct for intra-scan motion during a magnetic resonance scan when the computer program is executed on the suitably programmed computer system, the method comprising:
generating by a magnetic resonance scanner a magnetic field gradient and a radiofrequency signal for the magnetic resonance scan;
tracking by a motion tracking system one or more pose parameters of a subject and transmitting pose data corresponding to the tracked one or more pose parameters at a given time to the magnetic resonance scanner; calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the transmitted pose data and a gradient sequence used for the magnetic resonance scan;
applying by the magnetic resonance scanner the correction gradient to the subject prior to detecting signals emitted from the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan; and
detecting by the magnetic resonance scanner the signals emitted from the subject for data acquisition,
wherein the computer comprises a computer processor and an electronic storage medium.
126. The computer-readable, non-transitory storage medium of Claim 125, wherein the method further comprises comparing by an error correction module the transmitted pose data to final pose data and eliminate one or more residual errors in the calculation of the moment of the correction gradient, wherein the final orientation data is available after data acquisition.
127. The computer-readable, non-transitory storage medium of Claim 125, wherein the method further comprises updating by a geometry update module one or more geometric parameters based on the transmitted pose data to correct errors in the one or more geometric parameters due to movement of the subject.
128. The computer-readable, non-transitory storage medium of Claim 127, wherein the geometry update module is configured to update the one or more geometric parameters prior to one or more radiofrequency pulses.
129. The computer-readable, non-transitory storage medium of Claim 127, wherein the geometry update module is configured to update the one or more geometric parameters prior to each radiofrequency pulse.
130. The computer-readable, non-transitory storage medium of Claim 127, wherein the method further comprises comparing by an error correction module the transmitted pose data to final pose data and eliminating one or more residual errors in the one or more geometric parameters, wherein the final orientation data is available after data acquisition.
131. The computer-readable, non-transitory storage medium of Claim 125, wherein the method further comprises updating by a phase encoding update module one or more phase encoding gradients based on the transmitted pose data.
132. The computer-readable, non-transitory storage medium of Claim 131, wherein the method further comprises comparing by an error correction module the transmitted pose data to final pose data and eliminating one or more residual errors in the updates to the one or more phase encoding gradients, wherein the final orientation data is available after data acquisition.
133. The computer-readable, non-transitory storage medium of Claim 131, wherein the phase encoding update module is configured to update the one or more phase encoding gradients after excitation and prior to data acquisition by the magnetic resonance scanner.
134. The computer-readable, non-transitory storage medium of Claim 131, wherein the phase encoding update module is configured to update the one or more phase encoding gradients concurrently with data acquisition by the magnetic resonance scanner.
135. The computer-readable, non-transitory storage medium of Claim 125, wherein the method further comprises updating by a read encoding gradient update module one or more read encoding gradients based on the transmitted orientation data.
136. The computer-readable, non-transitory storage medium of Claim 135 wherein the method further comprises comparing by an error correction module the transmitted pose data to final pose data and eliminating one or more residual errors in the updates to the one or more read encoding gradients, wherein the final orientation data is available after data acquisition.
137. The computer-readable, non-transitory storage medium of Claim 135, wherein the read encoding update module is configured to update the one or more read encoding gradients after excitation and prior to data acquisition by the magnetic resonance scanner.
138. The computer-readable, non-transitory storage medium of Claim 135, wherein the read encoding gradient update module is configured to update the one or more read encoding gradients concurrently with data acquisition by the magnetic resonance scanner.
139. The computer-readable, non-transitory storage medium of Claim 125, wherein the moment of the correction gradient is calculated to reverse a first gradient moment, wherein the first gradient moment is calculated from the transmitted pose data according to: τ
M = R-1(t) - G(t) - dt
0
wherein R(t) is a rotation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
140. The computer-readable, non-transitory storage medium of Claim 125, wherein the method further comprises correcting by a phase correction module errors in one or more phases.
141. The computer-readable, non-transitory storage medium of Claim 140, wherein the phase correction module is configured to correct errors in the one or more phases based on:
Figure imgf000065_0001
wherein X(t) is a translation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
142. The computer-readable, non-transitory storage medium of Claim 125, wherein one or more of the transmitted pose data used to calculate the moment of the correction gradient is shifted in time to correct for one or more prediction errors related to the transmitted pose data.
143. The computer-readable, non-transitory storage medium of Claim 142, wherein the one or more prediction errors comprise lag time, noise, and changes in motion pattern.
144. The computer-readable, non-transitory storage medium of Claim 125, wherein the motion tracking system comprises a Moire Phase Tracking system.
145. The computer-readable, non-transitory storage medium of Claim 125, wherein the motion tracking system comprises a stereovision tracking system.
146. The computer-readable, non-transitory storage medium of Claim 125, wherein the correction gradient is an additional magnetic gradient to be applied to the subject for a period of time.
147. The computer-readable, non-transitory storage medium of Claim 125, wherein the correction gradient is applied in conjunction with another gradient.
148. The computer-readable, non-transitory storage medium of Claim 125, wherein the method is capable of correcting one or more errors due to movement of the subject occurring at greater than 10 mm per second.
149. A computer-readable, non-transitory storage medium having a computer program stored thereon for causing a suitably programmed computer system to process by one or more computer processors computer-program code by performing a method to correct for intra-scan motion during a magnetic resonance scan when the computer program is executed on the suitably programmed computer system, the method comprising:
receiving by a motion tracking module pose data of a subject from one or more motion tracking systems during the magnetic resonance scan of the subject; and calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan,
wherein the computer comprises a computer processor and an electronic storage medium.
150. The computer-readable, non-transitory storage medium of Claim 149, wherein the motion tracking module and the correction gradient calculation module are connected to a magnetic resonance system via a computer network.
151. The computer-readable, non-transitory storage medium of Claim 150, wherein the magnetic resonance system is configured to apply the correction gradient on the subject.
152. The computer-readable, non-transitory storage medium of Claim 149, wherein the correction gradient is an additional magnetic gradient to be applied to the subject for a period of time.
153. The computer-readable, non-transitory storage medium of Claim 149, wherein the correction gradient is applied in conjunction with another gradient.
154. The computer-readable, non-transitory storage medium of Claim 149, wherein the method further comprises updating by a geometry update module one or more geometric parameters based on the received pose data to correct errors in the one or more geometric parameters due to movement of the subject.
155. The computer-readable, non-transitory storage medium of Claim 149, wherein the method further comprises updating by a phase encoding update module one or more phase encoding gradients based on the received pose data.
156. The computer-readable, non-transitory storage medium of Claim 149, wherein the method further comprises updating by a read encoding gradient update module one or more read encoding gradients based on the received pose data.
157. The computer-readable, non-transitory storage medium of Claim 149, wherein the method further comprises comparing by an error correction module the received pose data to final pose data and eliminating one or more residual errors based on the comparison, wherein the final pose data is available after the magnetic resonance scan.
158. The computer-readable, non-transitory storage medium of Claim 157, wherein the one or more residual errors comprise errors in geometric orientation and signal phase.
159. The computer-readable, non-transitory storage medium of Claim 149, wherein the moment of the correction gradient is calculated to reverse a first gradient moment, wherein the first gradient moment is calculated from the received pose data according to:
Figure imgf000067_0001
wherein R(t) is a rotation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
160. The computer-readable, non-transitory storage medium of Claim 149, wherein the method further comprises correcting by a phase correction module errors in one or more phases.
161. The computer-readable, non-transitory storage medium of Claim 160, wherein the phase correction module is configured to correct errors in the one or more phases based on:
Figure imgf000067_0002
0
wherein X(t) is a translation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
162. The computer-readable, non-transitory storage medium of Claim 149, wherein the received pose data used to calculate the moment of the correction gradient is shifted in time to correct for one or more prediction errors related to the received pose data.
163. The computer-readable, non-transitory storage medium of Claim 149, wherein the method is capable of correcting one or more errors due to movement of the subject occurring at greater than 10 mm per second.
164. A computer-readable, non-transitory storage medium having a computer program stored thereon for causing a suitably programmed computer system to process by one or more computer processors computer-program code by performing a method to correct for intra-scan motion during a magnetic resonance scan when the computer program is executed on the suitably programmed computer system, the method comprising:
receiving by a motion tracking module pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and
calculating by an error correction module a gradient moment based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the calculated gradient moment, and wherein the one or more errors in the gradient moment are corrected during reconstruction,
wherein the computer comprises a computer processor and an electronic storage medium.
165. The computer-readable, non-transitory storage medium of Claim 164, wherein the motion tracking module and the error correction module are connected to a magnetic resonance system via a computer network.
166. The computer- implemented method of Claim 164, wherein the method further comprises updating by a geometry update module one or more geometric parameters based on the received pose data to correct errors in the one or more geometric parameters due to movement of the subject.
167. The computer-readable, non-transitory storage medium of Claim 164, wherein the method further comprises prospectively updating by a phase encoding update module one or more phase encoding gradients based on the received pose data.
168. The computer-readable, non-transitory storage medium of Claim 164, wherein the method further comprises prospectively updating by a read encoding gradient update module one or more read encoding gradients based on the received pose data.
169. The computer-readable, non-transitory storage medium of Claim 164, wherein the method further comprises calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in signal phase due to movement of the subject during the magnetic resonance scan.
170. The computer-readable, non-transitory storage medium of Claim 169, wherein the correction gradient is applied in conjunction with another gradient.
171. The computer-readable, non-transitory storage medium of Claim 169, wherein the moment of the correction gradient is calculated to reverse a first gradient moment, wherein the first gradient moment is calculated from the received pose data according to:
T
M = R-1(t) - G(t) - dt
0 wherein R(t) is a rotation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
172. The computer-readable, non-transitory storage medium of Claim 164, wherein the method further comprises correcting by a phase correction module errors in one or more phases.
173. The computer-readable, non-transitory storage medium of Claim 172, wherein the phase correction module is configured to correct errors in the one or more phases based on:
Figure imgf000069_0001
0
wherein X(t) is a translation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
174. The computer-readable, non-transitory storage medium of Claim 164, wherein the system is capable of correcting one or more errors due to movement of the subject occurring at greater than 10 mm per second.
175. A computer-readable, non-transitory storage medium having a computer program stored thereon for causing a suitably programmed computer system to process by one or more computer processors computer-program code by performing a method to correct for intra-scan motion during a magnetic resonance scan when the computer program is executed on the suitably programmed computer system, the method comprising:
receiving by a motion tracking module pose data of a subject from one or more motion tracking systems over a computer network during a magnetic resonance scan of the subject; and
calculating by an error correction module a phase based on the received pose data and a gradient sequence used for the magnetic resonance scan, wherein the error correction module is further configured to correct one or more errors in the phase, and wherein the one or more errors in the phase are corrected during reconstruction,
wherein the computer comprises a computer processor and an electronic storage medium.
176. The computer-readable, non-transitory storage medium of Claim 175, wherein the motion tracking module and the phase correction module are connected to a magnetic resonance system via a computer network.
177. The computer-readable, non-transitory storage medium of Claim 175, wherein the method further comprises updating by a geometry update module one or more geometric parameters based on the received pose data to correct errors in the one or more geometric parameters due to movement of the subject.
178. The computer-readable, non-transitory storage medium of Claim 175, wherein the method further comprises prospectively updating by a phase encoding update module one or more phase encoding gradients based on the received pose data.
179. The computer-readable, non-transitory storage medium of Claim 175, wherein the method further comprises prospectively updating by a read encoding gradient update module one or more read encoding gradients based on the received pose data.
180. The computer-readable, non-transitory storage medium of Claim 175, wherein the method further comprises calculating by a correction gradient calculation module a moment of a correction gradient to apply to the subject, wherein the moment of the correction gradient is calculated based on the received pose data and a gradient sequence used for the magnetic resonance scan, and wherein the correction gradient is to be applied to the subject to correct one or more initial errors in magnetic gradient moment due to movement of the subject during the magnetic resonance scan.
181. The computer-readable, non-transitory storage medium of Claim 180, wherein the correction gradient is applied in conjunction with another gradient.
182. The computer-readable, non-transitory storage medium of Claim 180, wherein the moment of the correction gradient is calculated to reverse a first gradient moment, wherein the first gradient moment is calculated from the received pose data according to:
Figure imgf000071_0001
0
wherein R(t) is a rotation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
183. The computer-readable, non-transitory storage medium of Claim 175, further comprising prospectively correcting by a phase correction module errors in one or more phases.
184. The computer-readable, non-transitory storage medium of Claim 183, wherein the phase correction module is configured to correct one or more errors in the phase based on:
Figure imgf000071_0002
0
wherein X(t) is a translation matrix of the subject, G(t) is a time series of gradients, and T is acquisition time.
185. The computer-readable, non-transitory storage medium of Claim 175, wherein the method further comprises calculating by the error correction module a gradient moment based on the received pose data and the gradient sequence, wherein the error correction module is further configured to correct one or more errors in the calculated gradient moment, and wherein the one or more errors in the gradient moment are corrected during reconstruction.
186. The computer-readable, non-transitory storage medium of Claim 175, wherein the method is capable of correcting one or more errors due to movement of the subject occurring at greater than 10 mm per second.
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Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9076212B2 (en) 2006-05-19 2015-07-07 The Queen's Medical Center Motion tracking system for real time adaptive imaging and spectroscopy
US9305365B2 (en) 2013-01-24 2016-04-05 Kineticor, Inc. Systems, devices, and methods for tracking moving targets
US9606209B2 (en) 2011-08-26 2017-03-28 Kineticor, Inc. Methods, systems, and devices for intra-scan motion correction
US9717461B2 (en) 2013-01-24 2017-08-01 Kineticor, Inc. Systems, devices, and methods for tracking and compensating for patient motion during a medical imaging scan
US9734589B2 (en) 2014-07-23 2017-08-15 Kineticor, Inc. Systems, devices, and methods for tracking and compensating for patient motion during a medical imaging scan
US9782141B2 (en) 2013-02-01 2017-10-10 Kineticor, Inc. Motion tracking system for real time adaptive motion compensation in biomedical imaging
US9943247B2 (en) 2015-07-28 2018-04-17 The University Of Hawai'i Systems, devices, and methods for detecting false movements for motion correction during a medical imaging scan
US10004462B2 (en) 2014-03-24 2018-06-26 Kineticor, Inc. Systems, methods, and devices for removing prospective motion correction from medical imaging scans
US10327708B2 (en) 2013-01-24 2019-06-25 Kineticor, Inc. Systems, devices, and methods for tracking and compensating for patient motion during a medical imaging scan
TWI678544B (en) * 2018-02-27 2019-12-01 鴻海精密工業股份有限公司 Magnetic resonance imaging device and dementia monitor system
US10716515B2 (en) 2015-11-23 2020-07-21 Kineticor, Inc. Systems, devices, and methods for tracking and compensating for patient motion during a medical imaging scan

Families Citing this family (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2010116782A1 (en) * 2009-03-30 2010-10-14 株式会社 日立製作所 Magnetic resonance device
US9329252B2 (en) * 2011-08-30 2016-05-03 The Board Of Trustees Of The Leland Stanford Junior University Apparatus for real-time phase correction for diffusion-weighted magnetic resonance imaging using adaptive RF pulses
US10874353B2 (en) * 2011-08-31 2020-12-29 Insightec, Ltd. Systems and methods for avoiding MRI-originated interference with concurrently used systems
FI20125277L (en) * 2012-03-14 2013-09-15 Mirasys Business Analytics Oy METHOD, SYSTEM AND COMPUTER SOFTWARE PRODUCT FOR COORDINATING VIDEO INFORMATION WITH OTHER MEASUREMENT INFORMATION
JP5752738B2 (en) * 2013-04-25 2015-07-22 ジーイー・メディカル・システムズ・グローバル・テクノロジー・カンパニー・エルエルシー Scan condition determining apparatus, magnetic resonance imaging apparatus, scan condition determining method, and program
WO2015124388A1 (en) * 2014-02-19 2015-08-27 Koninklijke Philips N.V. Motion adaptive visualization in medical 4d imaging
JP2017508556A (en) * 2014-03-28 2017-03-30 コーニンクレッカ フィリップス エヌ ヴェKoninklijke Philips N.V. EPI ghost correction for SENSE
DE102014210471B4 (en) * 2014-06-03 2018-11-08 Siemens Healthcare Gmbh A method of performing a magnetic resonance examination with a prospective motion correction and magnetic resonance system therefor
EP3353711A1 (en) * 2015-09-23 2018-08-01 Datalogic USA, Inc. Imaging systems and methods for tracking objects
DE102016200228A1 (en) * 2016-01-12 2017-07-13 Siemens Healthcare Gmbh Playing a magnetic resonance control sequence
DE102016204198B4 (en) * 2016-03-15 2018-06-07 Siemens Healthcare Gmbh Method for generating MR images with prospective motion correction and partial volume-specific weighting of the image information
US10545211B2 (en) * 2017-06-28 2020-01-28 Synaptive Medical (Barbados) Inc. Method of correcting gradient nonuniformity in gradient motion sensitive imaging applications
WO2020185757A1 (en) 2019-03-12 2020-09-17 University Of Cincinnati A system and method for motion correction of magnetic resonance image
EP3901649A1 (en) * 2020-04-20 2021-10-27 Siemens Healthcare GmbH Arrangement and method for motion correction in magnetic resonance imaging
US11925419B2 (en) * 2020-12-30 2024-03-12 Shanghai United Imaging Healthcare Co., Ltd. Systems and methods for position determination
US11794107B2 (en) * 2020-12-30 2023-10-24 Activision Publishing, Inc. Systems and methods for improved collision detection in video games

Family Cites Families (700)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3811213A (en) 1968-11-17 1974-05-21 Photo Motion Corp Moire motion illusion apparatus and method
US4689999A (en) 1985-07-26 1987-09-01 The Garrett Corporation Temperature compensated pressure transducer
US4724386A (en) * 1985-09-30 1988-02-09 Picker International, Inc. Centrally ordered phase encoding
FI870285A (en) 1987-01-22 1988-07-23 Outokumpu Oy FOERFARANDE FOER PLACERING AV SKIVFORMIGA FOEREMAOL SAMT ANORDNING FOER DETTA.
FR2623996A1 (en) 1987-12-08 1989-06-09 Thomson Csf PATIENT MONITORING DEVICE IN MEDICAL EXAMINING APPARATUS
US4953554A (en) 1988-03-04 1990-09-04 Resonex, Inc. Magnetic resonance imaging method
US6099522A (en) 1989-02-06 2000-08-08 Visx Inc. Automated laser workstation for high precision surgical and industrial interventions
US4988886A (en) 1989-04-06 1991-01-29 Eastman Kodak Company Moire distance measurement method and apparatus
JPH0323838A (en) 1989-06-21 1991-01-31 Toshiba Corp Magnetic resonance imaging apparatus
US5075562A (en) 1990-09-20 1991-12-24 Eastman Kodak Company Method and apparatus for absolute Moire distance measurements using a grating printed on or attached to a surface
US6405072B1 (en) 1991-01-28 2002-06-11 Sherwood Services Ag Apparatus and method for determining a location of an anatomical target with reference to a medical apparatus
AU6666894A (en) 1993-04-22 1994-11-08 Pixsys, Inc. System for locating relative positions of objects
JPH0775627A (en) 1993-06-11 1995-03-20 Hitachi Ltd Body motion follow-up measuring method in magnetic resonance diagnostic device
US5318026A (en) 1993-08-11 1994-06-07 Board Of Trustees Of The Leland Stanford Junior University Method and apparatus for tracking of deformable regions by phase contrast MRI
US5802202A (en) 1993-12-24 1998-09-01 Mazda Motor Corporation Method of determining three dimensional position of object and apparatus therefor
US5877732A (en) 1994-04-13 1999-03-02 Resonance Technology Co. Three-dimensional high resolution MRI video and audio system and method
EP0951874A3 (en) 1994-09-15 2000-06-14 Visualization Technology, Inc. Position tracking and imaging system for use in medical applications using a reference unit secured to a patients head
BR9509778A (en) 1994-11-28 1997-09-30 Analogic Corp Medical imaging system for use in ups
GB9500943D0 (en) 1994-12-01 1995-03-08 Popovich Milan M Optical position sensing system
US5666157A (en) 1995-01-03 1997-09-09 Arc Incorporated Abnormality detection and surveillance system
US6122541A (en) 1995-05-04 2000-09-19 Radionics, Inc. Head band for frameless stereotactic registration
US8330812B2 (en) 1995-05-30 2012-12-11 Simulated Percepts, Llc Method and apparatus for producing and storing, on a resultant non-transitory storage medium, computer generated (CG) video in correspondence with images acquired by an image acquisition device tracked in motion with respect to a 3D reference frame
US6181371B1 (en) 1995-05-30 2001-01-30 Francis J Maguire, Jr. Apparatus for inducing attitudinal head movements for passive virtual reality
US5515711A (en) 1995-06-26 1996-05-14 Mks Instruments, Inc. Pressure measurement and calibration apparatus using gravity-induced diaphragm deflection
DE19528436C2 (en) 1995-08-02 1997-07-03 Siemens Ag Procedure for tracking the movement of interventional instruments in an object with MR imaging
US5615677A (en) 1995-08-04 1997-04-01 The Board Of Trustees Of The Leland Stanford Junior University MRI tracking of cyclical motion by fourier integration of velocity
US6430997B1 (en) 1995-11-06 2002-08-13 Trazer Technologies, Inc. System and method for tracking and assessing movement skills in multidimensional space
DE29519078U1 (en) 1995-12-01 1996-01-25 Kelle Olaf Dr Device for detecting the spatial position of a human body part
US5835223A (en) 1996-01-05 1998-11-10 Electronic Packaging Services, Ltd. System for measuring surface flatness using shadow moire technology
US5889505A (en) 1996-04-04 1999-03-30 Yale University Vision-based six-degree-of-freedom computer input device
US6167296A (en) 1996-06-28 2000-12-26 The Board Of Trustees Of The Leland Stanford Junior University Method for volumetric image navigation
US5886257A (en) 1996-07-03 1999-03-23 The Charles Stark Draper Laboratory, Inc. Autonomous local vertical determination apparatus and methods for a ballistic body
US5728935A (en) 1996-08-14 1998-03-17 Czompo; Jozsef Method and apparatus for measuring gravity with lever arm correction
US5936722A (en) 1996-08-15 1999-08-10 Armstrong; Brian S. R. Apparatus and method for determining the angular orientation of an object
US5936723A (en) 1996-08-15 1999-08-10 Go Golf Orientation dependent reflector
US6384908B1 (en) 1996-08-15 2002-05-07 Go Sensors, Llc Orientation dependent radiation source
US6016439A (en) 1996-10-15 2000-01-18 Biosense, Inc. Method and apparatus for synthetic viewpoint imaging
CA2232997C (en) 1997-03-26 2001-07-10 Dalhousie University Dynamic target addressing system
US6044308A (en) 1997-06-13 2000-03-28 Huissoon; Jan Paul Method and device for robot tool frame calibration
EP2362286B1 (en) 1997-09-19 2015-09-02 Massachusetts Institute Of Technology Robotic apparatus
DE69738156T2 (en) 1997-09-27 2008-06-12 Brainlab Ag Method and device for taking a three-dimensional image of a body part
US5891060A (en) 1997-10-13 1999-04-06 Kinex Iha Corp. Method for evaluating a human joint
US6031888A (en) 1997-11-26 2000-02-29 Picker International, Inc. Fluoro-assist feature for a diagnostic imaging device
US6061644A (en) 1997-12-05 2000-05-09 Northern Digital Incorporated System for determining the spatial position and orientation of a body
US6057685A (en) 1997-12-09 2000-05-02 General Electric Company Method for correcting motion-induced errors in MR imaging
US6057680A (en) 1997-12-17 2000-05-02 General Electric Company Method for adjusting MR scan plane over cardiac cycle to track motion of coronary artery
WO1999038449A1 (en) 1998-01-28 1999-08-05 Cosman Eric R Optical object tracking system
US6289235B1 (en) 1998-03-05 2001-09-11 Wake Forest University Method and system for creating three-dimensional images using tomosynthetic computed tomography
US5947900A (en) 1998-04-13 1999-09-07 General Electric Company Dynamic scan plane tracking using MR position monitoring
US6298262B1 (en) 1998-04-21 2001-10-02 Neutar, Llc Instrument guidance for stereotactic surgery
US20050105772A1 (en) 1998-08-10 2005-05-19 Nestor Voronka Optical body tracker
DE19838590A1 (en) 1998-08-25 2000-03-09 Siemens Ag Magnetic resonance imaging for moving object
WO2000018287A1 (en) 1998-09-25 2000-04-06 Case Western Reserve University Acquired pendular nystagmus treatment device
US6088482A (en) 1998-10-22 2000-07-11 Symbol Technologies, Inc. Techniques for reading two dimensional code, including maxicode
US8788020B2 (en) 1998-10-23 2014-07-22 Varian Medical Systems, Inc. Method and system for radiation application
US6279579B1 (en) 1998-10-23 2001-08-28 Varian Medical Systems, Inc. Method and system for positioning patients for medical treatment procedures
US6937696B1 (en) 1998-10-23 2005-08-30 Varian Medical Systems Technologies, Inc. Method and system for predictive physiological gating
US6980679B2 (en) 1998-10-23 2005-12-27 Varian Medical System Technologies, Inc. Method and system for monitoring breathing activity of a subject
US6621889B1 (en) 1998-10-23 2003-09-16 Varian Medical Systems, Inc. Method and system for predictive physiological gating of radiation therapy
US6973202B2 (en) 1998-10-23 2005-12-06 Varian Medical Systems Technologies, Inc. Single-camera tracking of an object
AU771104B2 (en) 1998-10-23 2004-03-11 Varian Medical Systems Technologies, Inc. Method and system for physiological gating of radiation therapy
US6484131B1 (en) 1999-08-27 2002-11-19 Netmor Ltd. Localization and tracking system
US6285902B1 (en) 1999-02-10 2001-09-04 Surgical Insights, Inc. Computer assisted targeting device for use in orthopaedic surgery
US6778850B1 (en) 1999-03-16 2004-08-17 Accuray, Inc. Frameless radiosurgery treatment system and method
US6144875A (en) 1999-03-16 2000-11-07 Accuray Incorporated Apparatus and method for compensating for respiratory and patient motion during treatment
US6501981B1 (en) 1999-03-16 2002-12-31 Accuray, Inc. Apparatus and method for compensating for respiratory and patient motions during treatment
EP2275166A3 (en) 1999-03-24 2014-05-21 Second Sight Medical Products, Inc. Visual prosthesis
US7800758B1 (en) 1999-07-23 2010-09-21 Faro Laser Trackers, Llc Laser-based coordinate measuring device and laser-based method for measuring coordinates
MXPA01010656A (en) 1999-04-22 2002-06-04 Univ Johns Hopkins Cardiac motion tracking using cine harmonic phase (harp) magnetic resonance imaging.
US6292683B1 (en) 1999-05-18 2001-09-18 General Electric Company Method and apparatus for tracking motion in MR images
US7406214B2 (en) 1999-05-19 2008-07-29 Digimarc Corporation Methods and devices employing optical sensors and/or steganography
WO2000072039A1 (en) 1999-05-19 2000-11-30 National Research Council Of Canada Optical motion detection for mri
US7760905B2 (en) 1999-06-29 2010-07-20 Digimarc Corporation Wireless mobile phone with content processing
CA2377190A1 (en) 1999-07-23 2001-02-01 University Of Florida Ultrasonic guidance of target structures for medical procedures
WO2009079668A2 (en) 2007-12-17 2009-06-25 Rajasingham Arjuna Indraeswara Vehicle occupant support
US6568396B1 (en) 1999-10-26 2003-05-27 Philip F. Anthony 3 dimensional head apparatus and method for the treatment of BPPV
US6499488B1 (en) 1999-10-28 2002-12-31 Winchester Development Associates Surgical sensor
US6381485B1 (en) 1999-10-28 2002-04-30 Surgical Navigation Technologies, Inc. Registration of human anatomy integrated for electromagnetic localization
US6235038B1 (en) 1999-10-28 2001-05-22 Medtronic Surgical Navigation Technologies System for translation of electromagnetic and optical localization systems
US7024237B1 (en) 1999-10-29 2006-04-04 University Of Florida Research Foundation, Inc. Mask system and method for stereotactic radiotherapy and image guided procedures
AU2621601A (en) 1999-11-03 2001-05-14 Case Western Reserve University System and method for producing a three-dimensional model
US7747312B2 (en) 2000-01-04 2010-06-29 George Mason Intellectual Properties, Inc. System and method for automatic shape registration and instrument tracking
US6474159B1 (en) 2000-04-21 2002-11-05 Intersense, Inc. Motion-tracking
US6490475B1 (en) 2000-04-28 2002-12-03 Ge Medical Systems Global Technology Company, Llc Fluoroscopic tracking and visualization system
US6856827B2 (en) 2000-04-28 2005-02-15 Ge Medical Systems Global Technology Company, Llc Fluoroscopic tracking and visualization system
US6961608B2 (en) 2000-06-05 2005-11-01 Kabushiki Kaisha Toshiba Interventional MR imaging with detection and display of device position
DE10029592A1 (en) 2000-06-15 2001-12-20 Philips Corp Intellectual Pty MR imaging with motion compensation
DE10033063A1 (en) 2000-07-07 2002-01-24 Brainlab Ag Respiration compensated radiation treatment tracks target volume using markers and switches beam
FR2811791B1 (en) 2000-07-13 2002-11-22 France Telecom MOTION ESTIMATOR FOR CODING AND DECODING IMAGE SEQUENCES
EP1174076A3 (en) 2000-07-18 2002-10-16 BIOTRONIK Mess- und Therapiegeräte GmbH & Co Ingenieurbüro Berlin Device for automatically performing diagnostic and/or therapeutic actions in body cavities
JPWO2002022012A1 (en) 2000-09-11 2004-01-22 株式会社日立メディコ Magnetic resonance imaging system
ATE426357T1 (en) 2000-09-14 2009-04-15 Univ Leland Stanford Junior ASSESSING THE CONDITION OF A JOINT AND PLANNING TREATMENT
JP4515616B2 (en) 2000-09-25 2010-08-04 株式会社東芝 Magnetic resonance imaging system
DE10049414C2 (en) 2000-10-05 2002-09-26 Siemens Ag Magnetic resonance device with sound insulation
US6678413B1 (en) 2000-11-24 2004-01-13 Yiqing Liang System and method for object identification and behavior characterization using video analysis
US7209777B2 (en) 2000-11-30 2007-04-24 General Electric Company Method and apparatus for automated tracking of non-linear vessel movement using MR imaging
US7176440B2 (en) 2001-01-19 2007-02-13 Honeywell International Inc. Method and apparatus for detecting objects using structured light patterns
US20020115931A1 (en) 2001-02-21 2002-08-22 Strauss H. William Localizing intravascular lesions on anatomic images
DE10109511C2 (en) * 2001-02-28 2003-03-27 Max Planck Gesellschaft Method and device for obtaining data for diffusion-weighted magnetic resonance imaging
US6794869B2 (en) 2001-03-30 2004-09-21 General Electric Company Moving table MRI with frequency-encoding in the z-direction
US6897655B2 (en) 2001-03-30 2005-05-24 General Electric Company Moving table MRI with frequency-encoding in the z-direction
US6771068B2 (en) * 2001-05-10 2004-08-03 General Hospital Corporation System and method for providing real-time motion correction by utilizing navigators
US7259747B2 (en) 2001-06-05 2007-08-21 Reactrix Systems, Inc. Interactive video display system
US20020193685A1 (en) 2001-06-08 2002-12-19 Calypso Medical, Inc. Guided Radiation Therapy System
US7769430B2 (en) 2001-06-26 2010-08-03 Varian Medical Systems, Inc. Patient visual instruction techniques for synchronizing breathing with a medical procedure
US20030088177A1 (en) 2001-09-05 2003-05-08 Virtualscopics, Llc System and method for quantitative assessment of neurological diseases and the change over time of neurological diseases
US6771997B2 (en) 2001-09-11 2004-08-03 The Board Of Trustees Of The Leland Stanford Junior University Respiratory compensation in MRI coronary imaging using diminishing variance
US6687528B2 (en) 2001-09-28 2004-02-03 Ge Medical Systems Global Technology Company Llc Analysis of cardic MR relaxation time images with application to quantifying myocardial perfusion reserve indexes
US7209977B2 (en) 2001-10-01 2007-04-24 International Business Machines Corporation Method and apparatus for content-aware web switching
JP4127998B2 (en) 2001-11-15 2008-07-30 株式会社日立メディコ Magnetic resonance imaging system
US7945304B2 (en) 2001-11-20 2011-05-17 Feinberg David A Ultrasound within MRI scanners for guidance of MRI pulse sequences
GB0129465D0 (en) 2001-12-08 2002-01-30 Qinetiq Ltd Method for compensating for effects of object motion in an image
DE10161160A1 (en) 2001-12-13 2003-06-18 Tecmedic Gmbh Method for determining the orientation and relative position of a medical instrument in relation to a structure in the body of a breathing person or animal
US6711431B2 (en) 2002-02-13 2004-03-23 Kinamed, Inc. Non-imaging, computer assisted navigation system for hip replacement surgery
WO2003071950A1 (en) 2002-02-27 2003-09-04 Amid Srl M-tracking for space-time imaging
DE50201006D1 (en) 2002-04-16 2004-10-21 Brainlab Ag Marker for an instrument and method for locating a marker
US7260253B2 (en) 2002-04-19 2007-08-21 Visiongate, Inc. Method for correction of relative object-detector motion between successive views
US7835783B1 (en) 2002-04-22 2010-11-16 The United States Of America As Represented By The Department Of Health And Human Services Magnetic resonance imaging methods and apparatus for time-series motion tracking with inversion recovery compensation
US6707300B2 (en) * 2002-05-17 2004-03-16 Ge Medical Systems Global Technology Co., Llc Gradient non-linearity compensation in moving table MRI
US7894877B2 (en) 2002-05-17 2011-02-22 Case Western Reserve University System and method for adjusting image parameters based on device tracking
WO2003105709A1 (en) 2002-06-13 2003-12-24 Möller-Wedel GmbH Method and instrument for surgical navigation
GB2390792B (en) 2002-07-08 2005-08-31 Vision Rt Ltd Image processing system for use with a patient positioning device
US6933849B2 (en) 2002-07-09 2005-08-23 Fred Sawyer Method and apparatus for tracking objects and people
US7883415B2 (en) 2003-09-15 2011-02-08 Sony Computer Entertainment Inc. Method and apparatus for adjusting a view of a scene being displayed according to tracked head motion
US7107091B2 (en) 2002-07-25 2006-09-12 Orthosoft Inc. Multiple bone tracking
US7850526B2 (en) 2002-07-27 2010-12-14 Sony Computer Entertainment America Inc. System for tracking user manipulations within an environment
CA2633137C (en) 2002-08-13 2012-10-23 The Governors Of The University Of Calgary Microsurgical robot system
US20040171927A1 (en) 2002-08-26 2004-09-02 Steven Lowen Method and apparatus for measuring and compensating for subject motion during scanning
EP1543773B1 (en) 2002-09-12 2013-12-04 Hitachi Medical Corporation Biological tissue motion trace method and image diagnosis device using the trace method
US7561909B1 (en) 2002-09-16 2009-07-14 The United States Of America As Represented By The Department Of Health And Human Services MRI navigator methods and systems
US7706856B2 (en) 2002-09-27 2010-04-27 General Electric Company System and method for predictive thermal output control of a medical device
US6856828B2 (en) 2002-10-04 2005-02-15 Orthosoft Inc. CAS bone reference and less invasive installation method thereof
US8206219B2 (en) 2002-10-30 2012-06-26 Nike, Inc. Interactive gaming apparel for interactive gaming
US11082664B2 (en) 2004-07-06 2021-08-03 Tseng-Lu Chien Multiple functions LED night light
US7260426B2 (en) 2002-11-12 2007-08-21 Accuray Incorporated Method and apparatus for tracking an internal target region without an implanted fiducial
US7599730B2 (en) 2002-11-19 2009-10-06 Medtronic Navigation, Inc. Navigation system for cardiac therapies
US6889695B2 (en) 2003-01-08 2005-05-10 Cyberheart, Inc. Method for non-invasive heart treatment
US9033569B2 (en) 2010-11-22 2015-05-19 Tseng-Lu Chien Lamp holder has built-in night light
US7660623B2 (en) 2003-01-30 2010-02-09 Medtronic Navigation, Inc. Six degree of freedom alignment display for medical procedures
US7744528B2 (en) 2003-02-26 2010-06-29 Infinite Biomedical Technologies, Llc Methods and devices for endoscopic imaging
US7742804B2 (en) 2003-03-27 2010-06-22 Ivan Faul Means of tracking movement of bodies during medical treatment
US20110015521A1 (en) 2003-03-27 2011-01-20 Boulder Innovation Group, Inc. Means of Tracking Movement of Bodies During Medical Treatment
FR2854301B1 (en) 2003-04-24 2005-10-28 Yodea METHOD FOR TRANSMITTING DATA REPRESENTING THE POSITION IN THE SPACE OF A VIDEO CAMERA AND SYSTEM FOR IMPLEMENTING THE METHOD
US20100002070A1 (en) 2004-04-30 2010-01-07 Grandeye Ltd. Method and System of Simultaneously Displaying Multiple Views for Video Surveillance
US7171257B2 (en) 2003-06-11 2007-01-30 Accuray Incorporated Apparatus and method for radiosurgery
US6888924B2 (en) 2003-06-25 2005-05-03 General Electric Company Method, apparatus, and medium for calibration of tomosynthesis system geometry using fiducial markers with non-determined position
US7636486B2 (en) 2004-11-10 2009-12-22 Fotonation Ireland Ltd. Method of determining PSF using multiple instances of a nominally similar scene
JP4639045B2 (en) 2003-07-11 2011-02-23 財団法人先端医療振興財団 Non-invasive temperature distribution measuring method and apparatus for self-reference type and body movement tracking type by magnetic resonance tomography
US20050054910A1 (en) 2003-07-14 2005-03-10 Sunnybrook And Women's College Health Sciences Centre Optical image-based position tracking for magnetic resonance imaging applications
US7313430B2 (en) 2003-08-28 2007-12-25 Medtronic Navigation, Inc. Method and apparatus for performing stereotactic surgery
US8287373B2 (en) 2008-12-05 2012-10-16 Sony Computer Entertainment Inc. Control device for communicating visual information
US8323106B2 (en) 2008-05-30 2012-12-04 Sony Computer Entertainment America Llc Determination of controller three-dimensional location using image analysis and ultrasonic communication
US10279254B2 (en) 2005-10-26 2019-05-07 Sony Interactive Entertainment Inc. Controller having visually trackable object for interfacing with a gaming system
US7840253B2 (en) 2003-10-17 2010-11-23 Medtronic Navigation, Inc. Method and apparatus for surgical navigation
US7731360B2 (en) 2003-11-07 2010-06-08 Neuro Kinetics Portable video oculography system
US7251521B2 (en) * 2003-11-19 2007-07-31 Igc Medical Advances, Inc. Motion sensing MRI local coil
US9318012B2 (en) 2003-12-12 2016-04-19 Steve Gail Johnson Noise correcting patient fall risk state system and method for predicting patient falls
US7295007B2 (en) 2003-12-19 2007-11-13 Fraunhofer-Gesellschaft Zur Foerderung Der Angewandten Forschung E.V. Reducing movement artifacts in magnetic resonance measurements
JP2005205184A (en) 2003-12-22 2005-08-04 Pentax Corp Diagnosis supporting device
US7205526B2 (en) 2003-12-22 2007-04-17 Micron Technology, Inc. Methods of fabricating layered lens structures
WO2005077293A2 (en) 2004-02-10 2005-08-25 Koninklijke Philips Electronics N.V. A method, a system for generating a spatial roadmap for an interventional device and a quality control system for guarding the spatial accuracy thereof
US7819818B2 (en) 2004-02-11 2010-10-26 Jamshid Ghajar Cognition and motor timing diagnosis using smooth eye pursuit analysis
WO2005079122A1 (en) 2004-02-11 2005-08-25 Cstar Technologies Inc. Method and apparatus for cataloguing and poling movement in an environment for purposes of tracking and/or containment of infectious diseases
US7742077B2 (en) 2004-02-19 2010-06-22 Robert Bosch Gmbh Image stabilization system and method for a video camera
WO2005081842A2 (en) 2004-02-20 2005-09-09 University Of Florida Research Foundation, Inc. System for delivering conformal radiation therapy while simultaneously imaging soft tissue
US20050212753A1 (en) 2004-03-23 2005-09-29 Marvit David L Motion controlled remote controller
US20050212760A1 (en) 2004-03-23 2005-09-29 Marvit David L Gesture based user interface supporting preexisting symbols
US8229184B2 (en) 2004-04-16 2012-07-24 Validity Sensors, Inc. Method and algorithm for accurate finger motion tracking
US8048002B2 (en) 2004-04-27 2011-11-01 Jamshid Ghajar Method for improving cognition and motor timing
US8427538B2 (en) 2004-04-30 2013-04-23 Oncam Grandeye Multiple view and multiple object processing in wide-angle video camera
DE102004024470B4 (en) 2004-05-14 2013-10-10 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Reduction of motion artifacts in nuclear magnetic resonance measurements
US8214012B2 (en) 2004-06-17 2012-07-03 Psychology Software Tools, Inc. Magnetic resonance imaging having patient video, microphone and motion tracking
US7327865B2 (en) 2004-06-30 2008-02-05 Accuray, Inc. Fiducial-less tracking with non-rigid image registration
US20060004281A1 (en) 2004-06-30 2006-01-05 Michael Saracen Vest-based respiration monitoring system
US8095203B2 (en) 2004-07-23 2012-01-10 Varian Medical Systems, Inc. Data processing for real-time tracking of a target in radiation therapy
WO2006012645A2 (en) 2004-07-28 2006-02-02 Sarnoff Corporation Method and apparatus for total situational awareness and monitoring
US20060045310A1 (en) 2004-08-27 2006-03-02 General Electric Company System and method for tracking articulated body motion
US8406845B2 (en) 2004-09-01 2013-03-26 University Of Tennessee Research Foundation Method and apparatus for imaging tracking
DE602005017290D1 (en) 2004-09-06 2009-12-03 Bayerische Motoren Werke Ag DEVICE FOR DETECTING AN OBJECT ON A VEHICLE SEAT
US7925549B2 (en) 2004-09-17 2011-04-12 Accenture Global Services Limited Personalized marketing architecture
US7787935B2 (en) 2004-09-27 2010-08-31 General Electric Company System and method for correcting motion artifacts in imaging
US8989349B2 (en) 2004-09-30 2015-03-24 Accuray, Inc. Dynamic tracking of moving targets
US8027715B2 (en) 2004-10-02 2011-09-27 Accuray Incorporated Non-linear correlation models for internal target movement
US7925329B2 (en) 2004-10-08 2011-04-12 Proteus Biomedical, Inc. Implantable doppler tomography system
US7833221B2 (en) 2004-10-22 2010-11-16 Ethicon Endo-Surgery, Inc. System and method for treatment of tissue using the tissue as a fiducial
KR100638367B1 (en) 2004-10-30 2006-10-25 한국과학기술연구원 Autonomous vision display apparatus using pursuit of flying path about flying blimp screen or airship screen
EP1824385A4 (en) 2004-11-18 2009-08-12 Nedim Turan Sahin Mri as a therapeutic device
WO2006059669A1 (en) 2004-12-01 2006-06-08 Nidek Co., Ltd. Ophthalmic instrument
GB0426993D0 (en) 2004-12-09 2005-01-12 Council Cent Lab Res Councils Apparatus for depth-selective raman spectroscopy
US8095209B2 (en) 2005-01-06 2012-01-10 Braingate Co., Llc Biological interface system with gated control signal
US7889907B2 (en) 2005-01-12 2011-02-15 The Boeing Company Apparatus and methods for inspecting tape lamination
US7715604B2 (en) 2005-01-18 2010-05-11 Siemens Medical Solutions Usa, Inc. System and method for automatically registering three dimensional cardiac images with electro-anatomical cardiac mapping data
JP4689684B2 (en) 2005-01-21 2011-05-25 ジェスチャー テック,インコーポレイテッド Tracking based on movement
US7860301B2 (en) 2005-02-11 2010-12-28 Macdonald Dettwiler And Associates Inc. 3D imaging system
US7796154B2 (en) 2005-03-07 2010-09-14 International Business Machines Corporation Automatic multiscale image acquisition from a steerable camera
US20060241405A1 (en) 2005-03-09 2006-10-26 Aesculap Ag & Co. Kg Method and apparatus for performing an orthodepic stability test using a surgical navigation system
DE602005027128D1 (en) 2005-03-09 2011-05-05 Scherrer Inst Paul SYSTEM FOR SIMULTANEOUS RECORDING OF FIELD BEV (BEAM-EYE-VIEW) X-RAY IMAGES AND ADMINISTRATION OF PROTON THERAPY
ATE486332T1 (en) 2005-03-17 2010-11-15 British Telecomm METHOD FOR TRACKING OBJECTS IN A VIDEO SEQUENCE
US8139896B1 (en) 2005-03-28 2012-03-20 Grandeye, Ltd. Tracking moving objects accurately on a wide-angle video
US7760908B2 (en) 2005-03-31 2010-07-20 Honeywell International Inc. Event packaged video sequence
US8747382B2 (en) 2005-04-13 2014-06-10 University Of Maryland, Baltimore Techniques for compensating movement of a treatment target in a patient
US7978925B1 (en) 2005-04-16 2011-07-12 Apple Inc. Smoothing and/or locking operations in video editing
US8172573B2 (en) 2005-04-18 2012-05-08 Image Navigation Ltd Methods and apparatus for dental implantation
US7844094B2 (en) 2005-04-29 2010-11-30 Varian Medical Systems, Inc. Systems and methods for determining geometric parameters of imaging devices
US7946921B2 (en) 2005-05-23 2011-05-24 Microsoft Corproation Camera based orientation for mobile devices
US7603155B2 (en) 2005-05-24 2009-10-13 General Electric Company Method and system of acquiring images with a medical imaging device
ES2264383B1 (en) 2005-06-03 2007-11-16 Hospital Sant Joan De Deu OCULAR MOVEMENTS DEVICE DEVICE.
CN101194271B (en) 2005-06-09 2012-04-04 皇家飞利浦电子股份有限公司 Method and apparatus for distinguishing between clinically significant changes and artifacts in patient physiological information
WO2006137253A1 (en) 2005-06-22 2006-12-28 Matsushita Electric Industrial Co., Ltd. Image forming device, and image forming method
US7801330B2 (en) 2005-06-24 2010-09-21 Objectvideo, Inc. Target detection and tracking from video streams
US7713205B2 (en) 2005-06-29 2010-05-11 Accuray Incorporated Dynamic tracking of soft tissue targets with ultrasound images, without using fiducial markers
WO2007008715A2 (en) 2005-07-07 2007-01-18 Ingenious Targeting Laboratory, Inc. System for 3d monitoring and analysis of motion behavior of targets
CA2615659A1 (en) 2005-07-22 2007-05-10 Yogesh Chunilal Rathod Universal knowledge management and desktop search system
US20090041200A1 (en) 2005-07-23 2009-02-12 Tomotherapy Incorporated Radiation therapy imaging and delivery utilizing coordinated motion of jaws, gantry, and couch
EP1913333B1 (en) 2005-08-01 2012-06-06 Resonant Medical Inc. System and method for detecting drifts in calibrated tracking systems
US7668288B2 (en) 2005-08-15 2010-02-23 Digirad Corporation Discrete sampling of gamma ray field over multiple portions using multiple heads with spaces between the different portions
US7606392B2 (en) 2005-08-26 2009-10-20 Sony Corporation Capturing and processing facial motion data
US7720259B2 (en) 2005-08-26 2010-05-18 Sony Corporation Motion capture using primary and secondary markers
US20070049794A1 (en) 2005-09-01 2007-03-01 Ezc Medical Llc Visualization stylet for medical device applications having self-contained power source
US7944454B2 (en) 2005-09-07 2011-05-17 Fuji Xerox Co., Ltd. System and method for user monitoring interface of 3-D video streams from multiple cameras
US7787011B2 (en) 2005-09-07 2010-08-31 Fuji Xerox Co., Ltd. System and method for analyzing and monitoring 3-D video streams from multiple cameras
DE102005044033B4 (en) 2005-09-14 2010-11-18 Cas Innovations Gmbh & Co. Kg Positioning system for percutaneous interventions
US7689263B1 (en) 2005-09-15 2010-03-30 General Electric Company Method and apparatus for acquiring free-breathing MR images using navigator echo with saturation RF pulse
EP1932010A2 (en) 2005-09-29 2008-06-18 Koninklijke Philips Electronics N.V. System and method for acquiring magnetic resonance imaging (mri) data
US20080317313A1 (en) 2005-09-30 2008-12-25 Ut-Battelle, Llc System and method for tracking motion for generating motion corrected tomographic images
US8170302B1 (en) 2005-09-30 2012-05-01 Ut-Battelle, Llc System and method for generating motion corrected tomographic images
US8019170B2 (en) 2005-10-05 2011-09-13 Qualcomm, Incorporated Video frame motion-based automatic region-of-interest detection
US8208758B2 (en) 2005-10-05 2012-06-26 Qualcomm Incorporated Video sensor-based automatic region-of-interest detection
US8094193B2 (en) 2005-10-12 2012-01-10 New Vad, Llc Presentation video control system
US7806604B2 (en) 2005-10-20 2010-10-05 Honeywell International Inc. Face detection and tracking in a wide field of view
US20070093709A1 (en) 2005-10-26 2007-04-26 Abernathie Dennis L Surgical navigation markers
US7498811B2 (en) 2005-11-16 2009-03-03 Macfarlane Duncan L Apparatus and method for patient movement tracking
US7911207B2 (en) 2005-11-16 2011-03-22 Board Of Regents, The University Of Texas System Method for determining location and movement of a moving object
US7977942B2 (en) 2005-11-16 2011-07-12 Board Of Regents, The University Of Texas System Apparatus and method for tracking movement of a target
US8085302B2 (en) 2005-11-21 2011-12-27 Microsoft Corporation Combined digital and mechanical tracking of a person or object using a single video camera
US7173426B1 (en) 2005-11-29 2007-02-06 General Electric Company Optical link for transmitting data through air from a plurality of receiver coils in a magnetic resonance imaging system
US8021231B2 (en) 2005-12-02 2011-09-20 Walker Digital, Llc Problem gambling detection in tabletop games
US7751869B2 (en) 2005-12-09 2010-07-06 Boston Scientific Scimed, Inc. Radiation ablation tracking system and method
US8229166B2 (en) 2009-07-07 2012-07-24 Trimble Navigation, Ltd Image-based tracking
JP5307551B2 (en) 2005-12-28 2013-10-02 ニューロナノ アーベー Method and system for correcting tissue movement due to self-factors
US7602301B1 (en) 2006-01-09 2009-10-13 Applied Technology Holdings, Inc. Apparatus, systems, and methods for gathering and processing biometric and biomechanical data
US7878652B2 (en) 2006-01-24 2011-02-01 University Of Tennessee Research Foundation Adaptive photoscreening system
DE102006004197A1 (en) 2006-01-26 2007-08-09 Klett, Rolf, Dr.Dr. Method and device for recording body movements
JP5105848B2 (en) * 2006-02-06 2012-12-26 株式会社東芝 Magnetic resonance imaging apparatus and imaging condition setting method in magnetic resonance imaging apparatus
US8730156B2 (en) 2010-03-05 2014-05-20 Sony Computer Entertainment America Llc Maintaining multiple views on a shared stable virtual space
US8139029B2 (en) 2006-03-08 2012-03-20 Navisense Method and device for three-dimensional sensing
US20070239169A1 (en) 2006-03-17 2007-10-11 Perception Raisonnement Action En Medecine Reference marker and use in a motion tracking system
US8191359B2 (en) 2006-04-13 2012-06-05 The Regents Of The University Of California Motion estimation using hidden markov model processing in MRI and other applications
CA2651994C (en) 2006-05-17 2016-04-19 Koninklijke Philips Electronics N.V. Retrospective sorting of 4d ct into breathing phases based on geometric analysis of imaging fiducials
ES2569411T3 (en) 2006-05-19 2016-05-10 The Queen's Medical Center Motion tracking system for adaptive real-time imaging and spectroscopy
EP2026697B1 (en) 2006-05-22 2016-10-19 Philips Intellectual Property & Standards GmbH Motion-compensated coronary flow from projection imaging
FI120760B (en) 2006-05-31 2010-02-26 Palodex Group Oy Method and apparatus for medical X-ray imaging
CA2659586C (en) 2006-06-09 2014-12-02 Traxtal Inc. System for image-guided endovascular prosthesis and method for using same
US7742621B2 (en) 2006-06-13 2010-06-22 Delphi Technologies, Inc. Dynamic eye tracking system
CN101438218B (en) 2006-06-15 2011-11-23 诺基亚公司 Mobile equipment with virtual small keyboard
CA2653815C (en) 2006-06-23 2016-10-04 Imax Corporation Methods and systems for converting 2d motion pictures for stereoscopic 3d exhibition
JP4976756B2 (en) 2006-06-23 2012-07-18 キヤノン株式会社 Information processing method and apparatus
US20090209846A1 (en) 2006-06-28 2009-08-20 Roland Bammer Apparatus and method for real-time motion-compensated magnetic resonance imaging
GB2440993C (en) 2006-07-25 2014-03-19 Sony Comp Entertainment Europe Apparatus and method of interaction with a data processor
US20100231692A1 (en) 2006-07-31 2010-09-16 Onlive, Inc. System and method for performing motion capture and image reconstruction with transparent makeup
US8077914B1 (en) 2006-08-07 2011-12-13 Arkady Kaplan Optical tracking apparatus using six degrees of freedom
US20080049993A1 (en) 2006-08-25 2008-02-28 Restoration Robotics, Inc. System and method for counting follicular units
US7348776B1 (en) 2006-09-01 2008-03-25 The Board Of Trustees Of The Leland Stanford Junior University Motion corrected magnetic resonance imaging
GB2441550A (en) 2006-09-05 2008-03-12 Vision Rt Ltd Surface-imaging breathing monitor
US8316324B2 (en) 2006-09-05 2012-11-20 Navisense Method and apparatus for touchless control of a device
US8150498B2 (en) 2006-09-08 2012-04-03 Medtronic, Inc. System for identification of anatomical landmarks
US7925066B2 (en) 2006-09-13 2011-04-12 Nexstim Oy Method and apparatus for correcting an error in the co-registration of coordinate systems used to represent objects displayed during navigated brain stimulation
US8121356B2 (en) 2006-09-15 2012-02-21 Identix Incorporated Long distance multimodal biometric system and method
US8310656B2 (en) 2006-09-28 2012-11-13 Sony Computer Entertainment America Llc Mapping movements of a hand-held controller to the two-dimensional image plane of a display screen
EP1916538A3 (en) 2006-10-27 2011-02-16 Panasonic Electric Works Co., Ltd. Target moving object tracking device
US9891435B2 (en) 2006-11-02 2018-02-13 Sensics, Inc. Apparatus, systems and methods for providing motion tracking using a personal viewing device
CN101568293B (en) 2006-11-02 2012-03-21 海德堡工程有限责任公司 Method and apparatus for retinal diagnosis
JP4392507B2 (en) 2006-11-08 2010-01-06 国立大学法人東京工業大学 3D surface generation method
JP5028073B2 (en) 2006-11-29 2012-09-19 株式会社ニデック Cornea surgery device
CN101190128B (en) * 2006-11-30 2010-05-19 Ge医疗系统环球技术有限公司 Method and equipment for gathering magnetic resonance imaging data
US8214016B2 (en) 2006-12-12 2012-07-03 Perception Raisonnement Action En Medecine System and method for determining an optimal type and position of an implant
GB0625912D0 (en) 2006-12-22 2007-02-07 Bid Instr Ltd Method for visual field testing
US8189926B2 (en) 2006-12-30 2012-05-29 Videomining Corporation Method and system for automatically analyzing categories in a physical space based on the visual characterization of people
US8098889B2 (en) 2007-01-18 2012-01-17 Siemens Corporation System and method for vehicle detection and tracking
US8396654B1 (en) 2007-01-18 2013-03-12 Marvell International Ltd. Sensor positioning in handheld image translation device
US20080183074A1 (en) 2007-01-25 2008-07-31 Warsaw Orthopedic, Inc. Method and apparatus for coordinated display of anatomical and neuromonitoring information
US8331019B2 (en) 2007-01-26 2012-12-11 New York University Holographic microscopy of holographically trapped three-dimensional nanorod structures
US7839551B2 (en) 2007-01-26 2010-11-23 New York University Holographic microscopy of holographically trapped three-dimensional structures
US9055874B2 (en) 2007-01-27 2015-06-16 Xoran Technologies, Inc. Motion tracker to detect and correct for movement of a patient in a CT scanner
US8144148B2 (en) 2007-02-08 2012-03-27 Edge 3 Technologies Llc Method and system for vision-based interaction in a virtual environment
FR2912318B1 (en) 2007-02-13 2016-12-30 Parrot RECOGNITION OF OBJECTS IN A SHOOTING GAME FOR REMOTE TOYS
US20080212835A1 (en) 2007-03-01 2008-09-04 Amon Tavor Object Tracking by 3-Dimensional Modeling
EP2129284A4 (en) 2007-03-08 2012-11-28 Sync Rx Ltd Imaging and tools for use with moving organs
EP1970005B1 (en) 2007-03-15 2012-10-03 Xsens Holding B.V. A system and a method for motion tracking using a calibration unit
US8376226B2 (en) 2007-04-03 2013-02-19 International Business Machines Corporation System and method for interactive marketing to consumers
US8463006B2 (en) 2007-04-17 2013-06-11 Francine J. Prokoski System and method for using three dimensional infrared imaging to provide detailed anatomical structure maps
US8311611B2 (en) 2007-04-24 2012-11-13 Medtronic, Inc. Method for performing multiple registrations in a navigated procedure
US8301226B2 (en) 2007-04-24 2012-10-30 Medtronic, Inc. Method and apparatus for performing a navigated procedure
US20080273754A1 (en) 2007-05-04 2008-11-06 Leviton Manufacturing Co., Inc. Apparatus and method for defining an area of interest for image sensing
WO2008136947A1 (en) 2007-05-07 2008-11-13 Flextronics Ap, Llc Camera blade shutter module
US8260036B2 (en) 2007-05-09 2012-09-04 Honeywell International Inc. Object detection using cooperative sensors and video triangulation
US8417315B2 (en) 2007-05-14 2013-04-09 Varian Medical Systems, Inc. Marker systems with spaced apart surfaces or markers and methods of using the same
US8855719B2 (en) 2009-05-08 2014-10-07 Kopin Corporation Wireless hands-free computing headset with detachable accessories controllable by motion, body gesture and/or vocal commands
US20080287780A1 (en) 2007-05-16 2008-11-20 James Geoffrey Chase Integral based parameter identification applied to three dimensional tissue stiffness reconstruction in a digital image-based elasto-tomography system
US20080287807A1 (en) 2007-05-16 2008-11-20 James Geoffrey Chase Global motion invariant signatures for fast and accurate motion tracking in a digital image-based elasto-tomography system
US8213693B1 (en) 2007-05-16 2012-07-03 General Electric Company System and method to track and navigate a tool through an imaged subject
US8253770B2 (en) 2007-05-31 2012-08-28 Eastman Kodak Company Residential video communication system
US8024026B2 (en) 2007-05-31 2011-09-20 General Electric Company Dynamic reference method and system for use with surgical procedures
US8063929B2 (en) 2007-05-31 2011-11-22 Eastman Kodak Company Managing scene transitions for video communication
US8009200B2 (en) 2007-06-15 2011-08-30 Microsoft Corporation Multiple sensor input data synthesis
GB0712432D0 (en) 2007-06-26 2007-08-08 Isis Innovation Improvements in or relating to determination and display of material properties
US7908233B2 (en) 2007-06-29 2011-03-15 International Business Machines Corporation Method and apparatus for implementing digital video modeling to generate an expected behavior model
US7623623B2 (en) 2007-06-29 2009-11-24 Accuray Incorporated Non-collocated imaging and treatment in image-guided radiation treatment systems
CN101689304A (en) 2007-07-10 2010-03-31 皇家飞利浦电子股份有限公司 Object action capture system and method
US8939920B2 (en) 2007-07-13 2015-01-27 C-Rad Positioning Ab Patient monitoring at radiation machines
US8055049B2 (en) 2007-07-18 2011-11-08 Xoran Technologies, Inc. Motion correction for CT using marker projections
DE102007035176B4 (en) 2007-07-27 2010-03-18 Siemens Ag Method for recording and processing a sequence of temporally successive image data records and magnetic resonance apparatus
US7908060B2 (en) 2007-07-31 2011-03-15 International Business Machines Corporation Method and system for blind spot identification and warning utilizing portable and wearable devices
FR2919727B1 (en) 2007-08-03 2010-07-30 Valeo Vision METHOD FOR DETECTION BY A VEHICLE OF A VISIBILITY DISPERSING PHENOMENON
WO2009022270A2 (en) 2007-08-10 2009-02-19 Koninklijke Philips Electronics N.V. Motion detection in medical systems
US8221244B2 (en) 2007-08-14 2012-07-17 John B. French Table with sensors and smart card holder for automated gaming system and gaming cards
US8229163B2 (en) 2007-08-22 2012-07-24 American Gnc Corporation 4D GIS based virtual reality for moving target prediction
KR101363017B1 (en) 2007-08-23 2014-02-12 삼성전자주식회사 System and methed for taking pictures and classifying the pictures taken
JP2010541306A (en) 2007-08-27 2010-12-24 シャオ,チュエン Method and apparatus for simulating somatosensory experience in space
US20090061971A1 (en) 2007-08-31 2009-03-05 Visual Sports Systems Object Tracking Interface Device for Computers and Gaming Consoles
US8390729B2 (en) 2007-09-05 2013-03-05 International Business Machines Corporation Method and apparatus for providing a video image having multiple focal lengths
EP2043045B1 (en) 2007-09-20 2011-09-07 Delphi Technologies, Inc. Method for tracking an object
WO2009042637A2 (en) 2007-09-24 2009-04-02 Oregon Health & Science University Non-invasive location and tracking of tumors and other tissues for radiation therapy
US8195272B2 (en) 2007-09-24 2012-06-05 MRI Interventions, Inc. MRI-compatible patches and methods for using the same
WO2009042842A1 (en) 2007-09-26 2009-04-02 Cyberheart, Inc. Radiosurgical ablation of the myocardium
US8251908B2 (en) 2007-10-01 2012-08-28 Insightec Ltd. Motion compensated image-guided focused ultrasound therapy system
US8180428B2 (en) 2007-10-03 2012-05-15 Medtronic, Inc. Methods and systems for use in selecting cardiac pacing sites
EP2209526A1 (en) 2007-11-15 2010-07-28 Koninklijke Philips Electronics N.V. Method and apparatus for positional tracking of a therapeutic ultrasound transducer
US8791984B2 (en) 2007-11-16 2014-07-29 Scallop Imaging, Llc Digital security camera
US9521961B2 (en) 2007-11-26 2016-12-20 C. R. Bard, Inc. Systems and methods for guiding a medical instrument
US7944354B2 (en) 2007-11-29 2011-05-17 International Business Machines Corporation System and method for shopping cart security
WO2009074917A1 (en) 2007-12-11 2009-06-18 Koninklijke Philips Electronics N.V. Reducing motion artefacts in mri
US8041077B2 (en) 2007-12-18 2011-10-18 Robert Bosch Gmbh Method of motion detection and autonomous motion tracking using dynamic sensitivity masks in a pan-tilt camera
KR101409653B1 (en) 2007-12-18 2014-06-19 삼성전자주식회사 Method for photographing panorama picture in automation
US7712899B2 (en) 2007-12-21 2010-05-11 Sifi Diagnostic Spa Dual Scheimpflug system for three-dimensional analysis of an eye
US7792249B2 (en) 2007-12-23 2010-09-07 Oraya Therapeutics, Inc. Methods and devices for detecting, controlling, and predicting radiation delivery
US8022982B2 (en) 2008-01-02 2011-09-20 Sony Ericsson Mobile Communications Ab Camera system and method for operating a camera system
WO2009090885A1 (en) 2008-01-17 2009-07-23 Kabushiki Kaisha Toshiba Instructor support system
US20090185663A1 (en) 2008-01-22 2009-07-23 Gaines Jr Arthur J Equine CT Table
WO2009101566A1 (en) 2008-02-15 2009-08-20 Koninklijke Philips Electronics N.V. Compensating pressure sensor measurements
AU2009217348B2 (en) 2008-02-22 2014-10-09 Loma Linda University Medical Center Systems and methods for characterizing spatial distortion in 3D imaging systems
US8427552B2 (en) 2008-03-03 2013-04-23 Videoiq, Inc. Extending the operational lifetime of a hard-disk drive used in video data storage applications
EP2264679A4 (en) 2008-03-11 2013-08-21 Panasonic Corp Tag sensor system and sensor device, and object position estimating device and object position estimating method
WO2009116043A1 (en) 2008-03-18 2009-09-24 Atlas Invest Holdings Ltd. Method and system for determining familiarity with stimuli
JP5390377B2 (en) 2008-03-21 2014-01-15 淳 高橋 3D digital magnifier surgery support system
US7772569B2 (en) 2008-04-01 2010-08-10 The Jackson Laboratory 3D biplane microscopy
US20090253985A1 (en) 2008-04-07 2009-10-08 Magnetecs, Inc. Apparatus and method for lorentz-active sheath display and control of surgical tools
WO2009129457A1 (en) 2008-04-17 2009-10-22 The Government Of The United States Of America, As Represented By The Secretary, Department Of Health And Human Services Services, National Institutes Of Health Movement correction in mri using a camera
GB2459705B (en) 2008-05-01 2010-05-12 Sony Computer Entertainment Inc Media reproducing device, audio visual entertainment system and method
US7902825B2 (en) 2008-05-19 2011-03-08 The Board Of Trustees Of The Leland Stanford Junior University Motion corrected tensor magnetic resonance imaging
US8390291B2 (en) 2008-05-19 2013-03-05 The Board Of Regents, The University Of Texas System Apparatus and method for tracking movement of a target
US8175332B2 (en) 2008-05-22 2012-05-08 International Business Machines Corporation Upper troposphere and lower stratosphere wind direction, speed, and turbidity monitoring using digital imaging and motion tracking
AT506928B1 (en) 2008-05-28 2012-07-15 Kiwisecurity Software Gmbh METHOD OF VIDEO ANALYSIS
US8113991B2 (en) 2008-06-02 2012-02-14 Omek Interactive, Ltd. Method and system for interactive fitness training program
US8602857B2 (en) 2008-06-03 2013-12-10 Tweedletech, Llc Intelligent board game system with visual marker based game object tracking and identification
US8187097B1 (en) 2008-06-04 2012-05-29 Zhang Evan Y W Measurement and segment of participant's motion in game play
US8238651B2 (en) 2008-06-05 2012-08-07 Microsoft Corporation Image-guided abstraction of building facades
WO2009152055A2 (en) 2008-06-09 2009-12-17 Mako Surgical Corp. Self-detecting kinematic clamp assembly
JP5474953B2 (en) 2008-06-18 2014-04-16 ヴァイアップ リミテッド Tag product information
US8036425B2 (en) 2008-06-26 2011-10-11 Billy Hou Neural network-controlled automatic tracking and recognizing system and method
US8086026B2 (en) 2008-06-27 2011-12-27 Waldean Schulz Method and system for the determination of object positions in a volume
DE102008031159A1 (en) 2008-07-03 2010-01-07 Adc Automotive Distance Control Systems Gmbh Method for misalignment detection of a vehicle headlight with a camera
EP2306891A1 (en) 2008-07-08 2011-04-13 IT University of Copenhagen Eye gaze tracking
US8226574B2 (en) 2008-07-18 2012-07-24 Honeywell International Inc. Impaired subject detection system
US8334900B2 (en) 2008-07-21 2012-12-18 The Hong Kong University Of Science And Technology Apparatus and method of optical imaging for medical diagnosis
US8325228B2 (en) 2008-07-25 2012-12-04 International Business Machines Corporation Performing real-time analytics using a network processing solution able to directly ingest IP camera video streams
WO2010014887A1 (en) 2008-08-01 2010-02-04 The Mclean Hospital Corporation Method and apparatus for identifying a safe and efficacious dosing regimen
US7805987B1 (en) 2008-08-19 2010-10-05 Smith Bradley R System and method for pneumatic tire defect detection
CN102176888B (en) 2008-08-25 2015-11-25 苏黎世大学数学和自然科学部 Adjustable virtual reality system
DE102008046023B4 (en) 2008-09-05 2010-06-17 Siemens Aktiengesellschaft Tomography system and method for monitoring persons
US8216016B2 (en) 2008-09-12 2012-07-10 Sharp Kabushiki Kaisha Method of manufacturing display panel
US8483803B2 (en) 2008-09-15 2013-07-09 Varian Medical Systems, Inc. Systems and methods for tracking and targeting object in a patient using imaging techniques
US8223206B2 (en) 2008-10-15 2012-07-17 Flir Systems, Inc. Infrared camera filter wheel systems and methods
JP5634266B2 (en) 2008-10-17 2014-12-03 パナソニック株式会社 Flow line creation system, flow line creation apparatus and flow line creation method
US20100099981A1 (en) 2008-10-21 2010-04-22 Fishel Robert S Trans-Septal Catheterization Device And Method
US9095492B2 (en) 2008-11-19 2015-08-04 Industrial Research Limited Exercise device and system
WO2010059349A1 (en) 2008-11-21 2010-05-27 Cyberheart, Inc. Test object for the validation of tracking in the presence of motion
CA2747814C (en) 2008-11-21 2021-08-31 London Health Sciences Centre Research Inc. Hands-free pointer system
US8150063B2 (en) 2008-11-25 2012-04-03 Apple Inc. Stabilizing directional audio input from a moving microphone array
US8134597B2 (en) 2008-12-05 2012-03-13 Sony Ericsson Mobile Communications Ab Camera system with touch focus and method
GB0822605D0 (en) 2008-12-11 2009-01-21 Pneumacare Ltd Method and apparatus for monitoring an object
US20100149099A1 (en) 2008-12-12 2010-06-17 John Greer Elias Motion sensitive mechanical keyboard
JP5416960B2 (en) * 2008-12-17 2014-02-12 株式会社東芝 Magnetic resonance imaging system
US9142024B2 (en) 2008-12-31 2015-09-22 Lucasfilm Entertainment Company Ltd. Visual and physical motion sensing for three-dimensional motion capture
US20100179390A1 (en) 2009-01-12 2010-07-15 General Electric Company Collaborative tabletop for centralized monitoring system
US8290208B2 (en) 2009-01-12 2012-10-16 Eastman Kodak Company Enhanced safety during laser projection
US20100191631A1 (en) 2009-01-29 2010-07-29 Adrian Weidmann Quantitative media valuation method, system and computer program
JP5816098B2 (en) 2009-02-02 2015-11-18 アイサイト モバイル テクノロジーズ リミテッド System and method for object recognition and tracking in video streams
US8444564B2 (en) 2009-02-02 2013-05-21 Jointvue, Llc Noninvasive diagnostic system
US9569001B2 (en) 2009-02-03 2017-02-14 Massachusetts Institute Of Technology Wearable gestural interface
CN102317975B (en) 2009-02-17 2015-02-04 皇家飞利浦电子股份有限公司 Functional imaging
WO2010099516A1 (en) 2009-02-28 2010-09-02 Richard Welle Segmented fresnel solar concentrator
CN102341828B (en) 2009-03-06 2014-03-12 皇家飞利浦电子股份有限公司 Processing images of at least one living being
US20100231511A1 (en) 2009-03-10 2010-09-16 David L. Henty Interactive media system with multi-directional remote control and dual mode camera
CN102356417B (en) 2009-03-17 2014-09-10 马克思-普朗克科学促进协会 Teleoperation method and human robot interface for remote control of machine by human operator
US8368586B2 (en) 2009-03-26 2013-02-05 Tialinx, Inc. Person-borne improvised explosive device detection
KR101221449B1 (en) 2009-03-27 2013-01-11 한국전자통신연구원 Apparatus and method for calibrating image between cameras
US8253774B2 (en) 2009-03-30 2012-08-28 Microsoft Corporation Ambulatory presence features
JP5454570B2 (en) 2009-03-31 2014-03-26 日本電気株式会社 Tracking target determination device, tracking target determination method, and tracking target determination program
US8379927B2 (en) 2009-04-02 2013-02-19 Concept Systems Inc. Railcar unloading system
EP2239652A1 (en) 2009-04-07 2010-10-13 Keywords.de GmbH Providing an interactive visual representation on a display
US8428319B2 (en) 2009-04-24 2013-04-23 Siemens Aktiengesellschaft Automatic measurement of morphometric and motion parameters of the coronary tree from a rotational X-ray sequence
US8823775B2 (en) 2009-04-30 2014-09-02 Board Of Regents, The University Of Texas System Body surface imaging
US8477046B2 (en) 2009-05-05 2013-07-02 Advanced Technologies Group, LLC Sports telemetry system for collecting performance metrics and data
TW201040581A (en) 2009-05-06 2010-11-16 J Touch Corp Digital image capturing device with stereo image display and touch functions
US8953029B2 (en) 2009-05-08 2015-02-10 Sony Computer Entertainment America Llc Portable device interaction via motion sensitive controller
EP2427812A4 (en) 2009-05-08 2016-06-08 Kopin Corp Remote control of host application using motion and voice commands
EP2249288A3 (en) 2009-05-08 2014-05-21 Citysync Limited Object detection
US8705222B2 (en) 2009-05-11 2014-04-22 Nikon Corporation Compensating temperature effects in magnetic actuators
US8306663B2 (en) 2009-05-13 2012-11-06 Robotic Harvesting LLC Robot with 3D grasping capability
US9440591B2 (en) 2009-05-13 2016-09-13 Deere & Company Enhanced visibility system
JP5214533B2 (en) 2009-05-21 2013-06-19 富士フイルム株式会社 Person tracking method, person tracking apparatus, and person tracking program
US8744121B2 (en) 2009-05-29 2014-06-03 Microsoft Corporation Device for identifying and tracking multiple humans over time
US20100311512A1 (en) 2009-06-04 2010-12-09 Timothy James Lock Simulator with enhanced depth perception
JP5205337B2 (en) 2009-06-18 2013-06-05 富士フイルム株式会社 Target tracking device, image tracking device, operation control method thereof, and digital camera
DE102009030465A1 (en) 2009-06-23 2011-01-05 Carl Zeiss Meditec Ag Fixation control device and method for controlling a fixation of an eye
KR20100138725A (en) 2009-06-25 2010-12-31 삼성전자주식회사 Method and apparatus for processing virtual world
US8248372B2 (en) 2009-06-26 2012-08-21 Nokia Corporation Method and apparatus for activating one or more remote features
WO2011002874A1 (en) 2009-06-30 2011-01-06 University Of Utah Research Foundation Image reconstruction incorporating organ motion
CN101937289B (en) 2009-06-30 2013-06-05 鸿富锦精密工业(深圳)有限公司 Optical touch device
US8174375B2 (en) 2009-06-30 2012-05-08 The Hong Kong Polytechnic University Detection system for assisting a driver when driving a vehicle using a plurality of image capturing devices
US8860693B2 (en) 2009-07-08 2014-10-14 Apple Inc. Image processing for camera based motion tracking
US9019349B2 (en) 2009-07-31 2015-04-28 Naturalpoint, Inc. Automated collective camera calibration for motion capture
JP5388749B2 (en) * 2009-08-11 2014-01-15 株式会社東芝 Magnetic resonance imaging system
US8400398B2 (en) 2009-08-27 2013-03-19 Schlumberger Technology Corporation Visualization controls
US8218818B2 (en) 2009-09-01 2012-07-10 Behavioral Recognition Systems, Inc. Foreground object tracking
US8218819B2 (en) 2009-09-01 2012-07-10 Behavioral Recognition Systems, Inc. Foreground object detection in a video surveillance system
US20110054870A1 (en) 2009-09-02 2011-03-03 Honda Motor Co., Ltd. Vision Based Human Activity Recognition and Monitoring System for Guided Virtual Rehabilitation
US8548193B2 (en) 2009-09-03 2013-10-01 Palo Alto Research Center Incorporated Method and apparatus for navigating an electronic magnifier over a target document
GB2473624A (en) 2009-09-17 2011-03-23 Cammegh Ltd A roulette wheel system
US20130040720A1 (en) 2009-09-17 2013-02-14 Cammegh Limited Roulette Wheel System
KR101711619B1 (en) 2009-09-22 2017-03-02 페블스텍 리미티드 Remote control of computer devices
WO2011038170A2 (en) 2009-09-26 2011-03-31 Halliburton Energy Services, Inc. Downhole optical imaging tools and methods
US20110074675A1 (en) 2009-09-29 2011-03-31 Nokia Corporation Method and apparatus for initiating a feature based at least in part on the tracked movement
US9697746B2 (en) 2009-09-30 2017-07-04 National Ict Australia Limited Object tracking for artificial vision
US8116527B2 (en) 2009-10-07 2012-02-14 The United States Of America As Represented By The Secretary Of The Army Using video-based imagery for automated detection, tracking, and counting of moving objects, in particular those objects having image characteristics similar to background
GB0917688D0 (en) 2009-10-09 2009-11-25 Ucl Business Plc Tomosynthesis apparatus and method
IL201369A0 (en) 2009-10-11 2010-05-31 Michael Slatkine A bermatology apparatus
US8986211B2 (en) 2009-10-12 2015-03-24 Kona Medical, Inc. Energetic modulation of nerves
US8517962B2 (en) 2009-10-12 2013-08-27 Kona Medical, Inc. Energetic modulation of nerves
US20110092880A1 (en) 2009-10-12 2011-04-21 Michael Gertner Energetic modulation of nerves
US9174065B2 (en) 2009-10-12 2015-11-03 Kona Medical, Inc. Energetic modulation of nerves
KR101626065B1 (en) 2009-10-13 2016-05-31 삼성전자주식회사 Apparatus and method for markerless motion capturing
US8409098B2 (en) 2009-10-14 2013-04-02 St. Jude Medical, Atrial Fibrillation Division, Inc. Method and apparatus for collection of cardiac geometry based on optical or magnetic tracking
CA2718686C (en) 2009-10-20 2015-07-14 Imris Inc. Imaging system using markers
US8831279B2 (en) 2011-03-04 2014-09-09 Digimarc Corporation Smartphone-based methods and systems
US20110105893A1 (en) 2009-11-02 2011-05-05 General Electric Company Tissue tracking assembly and method
US8498689B2 (en) 2009-11-04 2013-07-30 International Business Machines Corporation Real time motion information capture in an MRI environment
EP2499550A1 (en) 2009-11-10 2012-09-19 Selex Sistemi Integrati S.p.A. Avatar-based virtual collaborative assistance
US20110115892A1 (en) 2009-11-13 2011-05-19 VisionBrite Technologies, Inc. Real-time embedded visible spectrum light vision-based human finger detection and tracking method
US8558899B2 (en) 2009-11-16 2013-10-15 The Aerospace Corporation System and method for super-resolution digital time delay and integrate (TDI) image processing
US20110117528A1 (en) 2009-11-18 2011-05-19 Marciello Robert J Remote physical therapy apparatus
US9176932B2 (en) 2009-11-25 2015-11-03 Koninklijke Philips N.V. Method for detecting falls and a fall detector
US9082177B2 (en) 2009-11-25 2015-07-14 Dental Imaging Technologies Corporation Method for tracking X-ray markers in serial CT projection images
US8801183B2 (en) 2009-11-30 2014-08-12 The Board Of Trustees Of The University Of Illinois Assessment of microvascular circulation
US8964033B2 (en) 2009-12-02 2015-02-24 Tata Consultancy Services Limited Cost-effective system and method for detecting, classifying and tracking the pedestrian using near infrared camera
US8232872B2 (en) 2009-12-03 2012-07-31 GM Global Technology Operations LLC Cross traffic collision alert system
US8235530B2 (en) 2009-12-07 2012-08-07 C-Rad Positioning Ab Object positioning with visual feedback
KR101027306B1 (en) 2009-12-14 2011-04-06 이명술 Apparatus of portable scanner and control method thereof
WO2011073989A1 (en) 2009-12-17 2011-06-23 Headway Ltd. "teach and repeat" method and apparatus for physiotherapeutic applications
US20110150271A1 (en) 2009-12-18 2011-06-23 Microsoft Corporation Motion detection using depth images
US8320621B2 (en) 2009-12-21 2012-11-27 Microsoft Corporation Depth projector system with integrated VCSEL array
US9041800B2 (en) 2009-12-30 2015-05-26 Robert Bosch Gmbh Confined motion detection for pan-tilt cameras employing motion detection and autonomous motion tracking
US20110160569A1 (en) 2009-12-31 2011-06-30 Amit Cohen system and method for real-time surface and volume mapping of anatomical structures
US8964013B2 (en) 2009-12-31 2015-02-24 Broadcom Corporation Display with elastic light manipulator
EP2348383B1 (en) 2009-12-31 2017-07-12 Sony Computer Entertainment Europe Limited System and method of virtual interaction
US8848977B2 (en) 2010-01-04 2014-09-30 The Board Of Trustees Of The Leland Stanford Junior University Method for optical pose detection
DE102010018899B4 (en) 2010-01-04 2014-08-21 MAX-PLANCK-Gesellschaft zur Förderung der Wissenschaften e.V. Apparatus and method for movement correction in MRI measurements
US8884813B2 (en) 2010-01-05 2014-11-11 The Invention Science Fund I, Llc Surveillance of stress conditions of persons using micro-impulse radar
US20110172060A1 (en) 2010-01-11 2011-07-14 Morales Anthony D Interactive systems and methods for reactive martial arts fitness training
US20110176723A1 (en) 2010-01-15 2011-07-21 Board Of Regents University Of Oklahoma Motion Correction in Cone-Beam CT by Tracking Internal and External Markers Using Cone-Beam Projection From a kV On-Board Imager: Four-Dimensional Cone-Beam CT and Tumor Tracking Implications
US8615127B2 (en) 2010-01-15 2013-12-24 Vanderbilt University System and method for point-based rigid registration with anisotropic weighting
US20120288852A1 (en) 2010-01-15 2012-11-15 Richard Willson Force Mediated Assays
US8334842B2 (en) 2010-01-15 2012-12-18 Microsoft Corporation Recognizing user intent in motion capture system
US8933884B2 (en) 2010-01-15 2015-01-13 Microsoft Corporation Tracking groups of users in motion capture system
US8284157B2 (en) 2010-01-15 2012-10-09 Microsoft Corporation Directed performance in motion capture system
US8659658B2 (en) 2010-02-09 2014-02-25 Microsoft Corporation Physical interaction zone for gesture-based user interfaces
US8954132B2 (en) 2010-02-12 2015-02-10 Jean P. HUBSCHMAN Methods and systems for guiding an emission to a target
US9522316B2 (en) 2010-02-12 2016-12-20 Bright Cloud International Corp. Instrumented therapy table and system
MX2012009436A (en) 2010-02-15 2012-12-05 Wavelight Gmbh Method for determining deviations between coordinate systems of various technical systems.
US8916811B2 (en) 2010-02-16 2014-12-23 Western Gas And Electric Company Integrated electronics housing for a solar array
US10178290B2 (en) 2010-02-17 2019-01-08 Sri International Method and apparatus for automatically acquiring facial, ocular, and iris images from moving subjects at long-range
US9687200B2 (en) 2010-06-08 2017-06-27 Accuray Incorporated Radiation treatment delivery system with translatable ring gantry
US20110207089A1 (en) 2010-02-25 2011-08-25 Lagettie David Alfred A Firearm training systems and methods of using the same
WO2011107987A1 (en) 2010-03-02 2011-09-09 Elbit Systems Ltd. Image gated camera for detecting objects in a marine environment
US20110230755A1 (en) 2010-03-04 2011-09-22 Macfarlane Duncan Single camera motion measurement and monitoring for magnetic resonance applications
US20110216180A1 (en) 2010-03-05 2011-09-08 Alessandro Pasini Method and system for obtaining improved computed tomographic reconstructions
US8614663B2 (en) 2010-03-15 2013-12-24 Empire Technology Development, Llc Selective motor control classification
WO2011113441A2 (en) 2010-03-18 2011-09-22 Rigshospitalet Optical motion tracking of an object
WO2011115727A1 (en) 2010-03-18 2011-09-22 Ohm Technologies Llc Method and apparatus for training brain development disorders
JP5394296B2 (en) 2010-03-25 2014-01-22 富士フイルム株式会社 Imaging apparatus and image processing method
US8320622B2 (en) 2010-03-29 2012-11-27 Sharp Laboratories Of America, Inc. Color gradient object tracking
US9820695B2 (en) 2010-03-29 2017-11-21 St. Jude Medical International Holding S.àr.l. Method for detecting contact with the wall of a region of interest
US9901828B2 (en) 2010-03-30 2018-02-27 Sony Interactive Entertainment America Llc Method for an augmented reality character to maintain and exhibit awareness of an observer
US20110245659A1 (en) 2010-04-01 2011-10-06 Sonosite, Inc. Systems and methods to assist with internal positioning of instruments
TWI478006B (en) 2010-04-13 2015-03-21 Hon Hai Prec Ind Co Ltd Cursor control device, display device and portable electronic device
WO2011128766A2 (en) 2010-04-13 2011-10-20 Picard Frederic Methods and systems for object tracking
US20130102879A1 (en) 2010-04-14 2013-04-25 Universitaetsklinikum Freiburg Method For Correcting Susceptibility-Induced Image Artifacts In MRI After Prospective Motion Correction
JP5523182B2 (en) 2010-04-20 2014-06-18 キヤノン株式会社 Video editing apparatus and video editing method
KR101334107B1 (en) 2010-04-22 2013-12-16 주식회사 굿소프트웨어랩 Apparatus and Method of User Interface for Manipulating Multimedia Contents in Vehicle
US8351651B2 (en) 2010-04-26 2013-01-08 Microsoft Corporation Hand-location post-process refinement in a tracking system
US8284847B2 (en) 2010-05-03 2012-10-09 Microsoft Corporation Detecting motion for a multifunction sensor device
US9706948B2 (en) 2010-05-06 2017-07-18 Sachin Bhandari Inertial sensor based surgical navigation system for knee replacement surgery
WO2011140993A1 (en) 2010-05-12 2011-11-17 北京星河易达科技有限公司 Intelligent traffic safety system based on comprehensive state detection and decision method thereof
US8525876B2 (en) 2010-05-12 2013-09-03 Visionbrite Technologies Inc. Real-time embedded vision-based human hand detection
US8625107B2 (en) 2010-05-19 2014-01-07 Uwm Research Foundation, Inc. Target for motion tracking system
US8937592B2 (en) 2010-05-20 2015-01-20 Samsung Electronics Co., Ltd. Rendition of 3D content on a handheld device
US8306274B2 (en) 2010-05-25 2012-11-06 The Aerospace Corporation Methods for estimating peak location on a sampled surface with improved accuracy and applications to image correlation and registration
US8751215B2 (en) 2010-06-04 2014-06-10 Microsoft Corporation Machine based sign language interpreter
US20110298708A1 (en) 2010-06-07 2011-12-08 Microsoft Corporation Virtual Touch Interface
EP2395413B1 (en) 2010-06-09 2018-10-03 The Boeing Company Gesture-based human machine interface
US20110304706A1 (en) 2010-06-09 2011-12-15 Border John N Video camera providing videos with perceived depth
US20110304541A1 (en) 2010-06-11 2011-12-15 Navneet Dalal Method and system for detecting gestures
CN102939051A (en) 2010-06-13 2013-02-20 安吉奥梅特里克斯公司 Methods and systems for determining vascular bodily lumen information and guiding medical devices
US8670029B2 (en) 2010-06-16 2014-03-11 Microsoft Corporation Depth camera illuminator with superluminescent light-emitting diode
US8558873B2 (en) 2010-06-16 2013-10-15 Microsoft Corporation Use of wavefront coding to create a depth image
US8836723B2 (en) 2010-06-18 2014-09-16 Vantage Surgical Systems, Inc. Augmented reality methods and systems including optical merging of a plurality of component optical images
US9516207B2 (en) 2010-06-24 2016-12-06 Marc S. Lemchen Exam-cam robotic systems and methods
US9241657B2 (en) 2010-06-30 2016-01-26 Brainlab Ag Medical image registration using a rigid inner body surface
US20120002112A1 (en) 2010-07-02 2012-01-05 Sony Corporation Tail the motion method of generating simulated strobe motion videos and pictures using image cloning
WO2012005392A1 (en) 2010-07-06 2012-01-12 Lg Electronics Inc. Object recognition and tracking based apparatus and method
US8531355B2 (en) 2010-07-23 2013-09-10 Gregory A. Maltz Unitized, vision-controlled, wireless eyeglass transceiver
US8531394B2 (en) 2010-07-23 2013-09-10 Gregory A. Maltz Unitized, vision-controlled, wireless eyeglasses transceiver
US20120027226A1 (en) 2010-07-30 2012-02-02 Milford Desenberg System and method for providing focused directional sound in an audio system
WO2012019162A1 (en) 2010-08-06 2012-02-09 Accuray, Inc. Systems and methods for real-time tumor tracking during radiation treatment using ultrasound imaging
US8463075B2 (en) 2010-08-11 2013-06-11 International Business Machines Corporation Dynamically resizing text area on a display device
TWI432925B (en) 2010-08-17 2014-04-01 Pixart Imaging Inc Interaction control system, method for detecting motion of object, host apparatus and control method thereof
US8532367B2 (en) 2010-08-17 2013-09-10 Raytheon Company System and method for 3D wireframe reconstruction from video
US9129426B2 (en) 2010-08-31 2015-09-08 General Electric Company Motion compensation in image processing
US20120057640A1 (en) 2010-09-02 2012-03-08 Fang Shi Video Analytics for Security Systems and Methods
US20120056982A1 (en) 2010-09-08 2012-03-08 Microsoft Corporation Depth camera based on structured light and stereo vision
US8736516B2 (en) 2010-09-20 2014-05-27 Kopin Corporation Bluetooth or other wireless interface with power management for head mounted display
US8862186B2 (en) 2010-09-21 2014-10-14 Kopin Corporation Lapel microphone micro-display system incorporating mobile information access system
US8600123B2 (en) 2010-09-24 2013-12-03 General Electric Company System and method for contactless multi-fingerprint collection
US20120075166A1 (en) 2010-09-29 2012-03-29 Samsung Electronics Co. Ltd. Actuated adaptive display systems
US20120083314A1 (en) 2010-09-30 2012-04-05 Ng Hock M Multimedia Telecommunication Apparatus With Motion Tracking
US8754925B2 (en) 2010-09-30 2014-06-17 Alcatel Lucent Audio source locator and tracker, a method of directing a camera to view an audio source and a video conferencing terminal
US8953847B2 (en) 2010-10-01 2015-02-10 Saab Ab Method and apparatus for solving position and orientation from correlated point features in images
US8509982B2 (en) 2010-10-05 2013-08-13 Google Inc. Zone driving
US8718346B2 (en) 2011-10-05 2014-05-06 Saferay Spine Llc Imaging system and method for use in surgical and interventional medical procedures
CN103153223B (en) 2010-10-08 2016-09-14 皇家飞利浦电子股份有限公司 The flexible cable with integrated sensor followed the trail of for dynamic instrument
TWI466545B (en) 2010-10-12 2014-12-21 Hon Hai Prec Ind Co Ltd Image capturing device and image monitoring method using the image capturing device
TW201216711A (en) 2010-10-12 2012-04-16 Hon Hai Prec Ind Co Ltd TOF image capturing device and image monitoring method using the TOF image capturing device
US20120092502A1 (en) 2010-10-13 2012-04-19 Mysnapcam, Llc Systems and methods for monitoring presence and movement
US9628755B2 (en) 2010-10-14 2017-04-18 Microsoft Technology Licensing, Llc Automatically tracking user movement in a video chat application
US9484065B2 (en) 2010-10-15 2016-11-01 Microsoft Technology Licensing, Llc Intelligent determination of replays based on event identification
US9113817B2 (en) 2010-10-20 2015-08-25 Siemens Medical Solutions Usa, Inc. System for locating anatomical objects in ultrasound imaging
US8896667B2 (en) 2010-10-25 2014-11-25 Aptina Imaging Corporation Stereoscopic imaging systems with convergence control for reducing conflicts between accomodation and convergence
US8400490B2 (en) 2010-10-30 2013-03-19 Hewlett-Packard Development Company, L.P. Framing an object for video conference
US20120108909A1 (en) 2010-11-03 2012-05-03 HeadRehab, LLC Assessment and Rehabilitation of Cognitive and Motor Functions Using Virtual Reality
US9529424B2 (en) 2010-11-05 2016-12-27 Microsoft Technology Licensing, Llc Augmented reality with direct user interaction
US20120113223A1 (en) 2010-11-05 2012-05-10 Microsoft Corporation User Interaction in Augmented Reality
US20120119999A1 (en) 2010-11-11 2012-05-17 Harris Scott C Adaptive Keyboard for portable device
GB2485390A (en) 2010-11-12 2012-05-16 Sony Corp Video Surveillance System that Detects Changes by Comparing a Current Image with a Reference Image
US8667519B2 (en) 2010-11-12 2014-03-04 Microsoft Corporation Automatic passive and anonymous feedback system
US20120120277A1 (en) 2010-11-16 2012-05-17 Apple Inc. Multi-point Touch Focus
US10560621B2 (en) 2010-11-19 2020-02-11 Symbol Technologies, Llc Methods and apparatus for controlling a networked camera
US9019239B2 (en) 2010-11-29 2015-04-28 Northrop Grumman Systems Corporation Creative design systems and methods
WO2012075155A2 (en) 2010-12-02 2012-06-07 Ultradent Products, Inc. System and method of viewing and tracking stereoscopic video images
US8711210B2 (en) 2010-12-14 2014-04-29 Raytheon Company Facial recognition using a sphericity metric
US20120156661A1 (en) 2010-12-16 2012-06-21 Lockheed Martin Corporation Method and apparatus for gross motor virtual feedback
US8644995B2 (en) 2010-12-17 2014-02-04 Western Gas And Electric Company Wireless local area network for a concentrated photovoltaic system
US20120154511A1 (en) 2010-12-20 2012-06-21 Shi-Ping Hsu Systems and methods for providing geographically distributed creative design
US9147260B2 (en) 2010-12-20 2015-09-29 International Business Machines Corporation Detection and tracking of moving objects
EP2469841A1 (en) 2010-12-22 2012-06-27 Thomson Licensing Setting a feature from the main menu of an application
US9123316B2 (en) 2010-12-27 2015-09-01 Microsoft Technology Licensing, Llc Interactive content creation
KR101811219B1 (en) 2011-01-10 2017-12-22 삼성전자 주식회사 Method and apparatus for controlling a portable terminal using a finger tracking
US8570320B2 (en) 2011-01-31 2013-10-29 Microsoft Corporation Using a three-dimensional environment model in gameplay
US20120200676A1 (en) 2011-02-08 2012-08-09 Microsoft Corporation Three-Dimensional Display with Motion Parallax
US9686452B2 (en) 2011-02-16 2017-06-20 Robert Bosch Gmbh Surveillance camera with integral large-domain sensor
US20120220233A1 (en) 2011-02-28 2012-08-30 Qualcomm Incorporated Ranging with body motion capture
JP5848507B2 (en) 2011-03-08 2016-01-27 キヤノン株式会社 Image capturing apparatus and method with tracking function
US20120242816A1 (en) 2011-03-24 2012-09-27 Arnaldo Zael Cruz Recognition system for firearms
US8718748B2 (en) 2011-03-29 2014-05-06 Kaliber Imaging Inc. System and methods for monitoring and assessing mobility
CN103493106B (en) 2011-03-29 2017-11-07 高通股份有限公司 Come hand is optionally covered to the method and apparatus on the virtual projection on physical surface using bone tracking
DE102011007574B4 (en) * 2011-04-18 2012-12-06 Universitätsklinikum Freiburg Method for quasi-continuous dynamic motion correction in measurements of magnetic resonance
US9224278B2 (en) 2011-04-18 2015-12-29 Xerox Corporation Automated method and system for detecting the presence of a lit cigarette
CN103562791A (en) 2011-04-18 2014-02-05 眼见360股份有限公司 Apparatus and method for panoramic video imaging with mobile computing devices
US20120277001A1 (en) 2011-04-28 2012-11-01 Microsoft Corporation Manual and Camera-based Game Control
US8702507B2 (en) 2011-04-28 2014-04-22 Microsoft Corporation Manual and camera-based avatar control
US8457355B2 (en) 2011-05-05 2013-06-04 International Business Machines Corporation Incorporating video meta-data in 3D models
US8306267B1 (en) 2011-05-09 2012-11-06 Google Inc. Object tracking
US8790269B2 (en) 2011-05-09 2014-07-29 Xerox Corporation Monitoring respiration with a thermal imaging system
CN102789642B (en) 2011-05-16 2017-08-25 索尼公司 Direction of extinction determines method and apparatus, camera self-calibration method and device
US9158976B2 (en) 2011-05-18 2015-10-13 International Business Machines Corporation Efficient retrieval of anomalous events with priority learning
US8788973B2 (en) 2011-05-23 2014-07-22 Microsoft Corporation Three-dimensional gesture controlled avatar configuration interface
US8666738B2 (en) 2011-05-24 2014-03-04 Alcatel Lucent Biometric-sensor assembly, such as for acoustic reflectometry of the vocal tract
US8823639B2 (en) 2011-05-27 2014-09-02 Disney Enterprises, Inc. Elastomeric input device
US9245307B2 (en) 2011-06-01 2016-01-26 Empire Technology Development Llc Structured light projection for motion detection in augmented reality
KR101073076B1 (en) 2011-06-10 2011-10-12 주식회사 창성에이스산업 Fire monitoring system and method using compound camera
US20120315016A1 (en) 2011-06-12 2012-12-13 Hei Tao Fung Multi-Purpose Image and Video Capturing Device
US20120319989A1 (en) 2011-06-20 2012-12-20 Chris Argiro Video-game controller assemblies designed for progressive control of actionable-objects displayed on touchscreens: expanding the method and breadth of touch-input delivery
DE102012208748B4 (en) 2011-06-21 2023-07-13 International Business Machines Corporation Method and system for remote control of functions of a mouse pointer of a computer unit
US20120326966A1 (en) 2011-06-21 2012-12-27 Qualcomm Incorporated Gesture-controlled technique to expand interaction radius in computer vision applications
CN103607972B (en) 2011-06-22 2016-08-17 新特斯有限责任公司 Ultrasound CT registration for location
US8681223B2 (en) 2011-06-24 2014-03-25 Honeywell International Inc. Video motion detection, analysis and threat detection device and method
US20130002879A1 (en) 2011-07-01 2013-01-03 Sensormatics Electronics, Llc Systems and methods for tracking a commodity
RU2455676C2 (en) 2011-07-04 2012-07-10 Общество с ограниченной ответственностью "ТРИДИВИ" Method of controlling device using gestures and 3d sensor for realising said method
US8825089B2 (en) 2011-07-08 2014-09-02 Matthew R. Godfrey Systems and methods for tracking and monitoring an electronic device
US8948447B2 (en) 2011-07-12 2015-02-03 Lucasfilm Entertainment Companyy, Ltd. Scale independent tracking pattern
US8179604B1 (en) 2011-07-13 2012-05-15 Google Inc. Wearable marker for passive interaction
US20130024819A1 (en) 2011-07-18 2013-01-24 Fuji Xerox Co., Ltd. Systems and methods for gesture-based creation of interactive hotspots in a real world environment
US8636361B2 (en) 2011-07-20 2014-01-28 National Taiwan University Learning-based visual attention prediction system and method thereof
US9084565B2 (en) 2011-07-29 2015-07-21 Wisconsin Alumni Research Foundation Hand-function therapy system with sensory isolation
US20130033700A1 (en) 2011-08-05 2013-02-07 Abdelbasset Hallil Radiation dosimeter with localization means and methods
US9554866B2 (en) 2011-08-09 2017-01-31 Covidien Lp Apparatus and method for using a remote control system in surgical procedures
KR20130021194A (en) 2011-08-22 2013-03-05 삼성전자주식회사 Magnetic resonance imaging (mri) system and method for controlling the same
US9606209B2 (en) 2011-08-26 2017-03-28 Kineticor, Inc. Methods, systems, and devices for intra-scan motion correction
WO2013036632A1 (en) 2011-09-09 2013-03-14 Thales Avionics, Inc. Eye tracking control of vehicle entertainment systems
US8903132B2 (en) 2011-09-12 2014-12-02 2343127 Ontario Inc. Efficient system and method for body part detection and tracking
US8849200B2 (en) 2011-09-14 2014-09-30 Telefonaktiebolaget L M Ericsson (Publ) Controlling pairing of entities responsive to motion challenges and responses
US9918681B2 (en) 2011-09-16 2018-03-20 Auris Surgical Robotics, Inc. System and method for virtually tracking a surgical tool on a movable display
US20130070257A1 (en) 2011-09-18 2013-03-21 Fidelity Art Research Limited Three-Dimensional Scanning System
US9330477B2 (en) 2011-09-22 2016-05-03 Digital Surgicals Pte. Ltd. Surgical stereo vision systems and methods for microsurgery
WO2013044137A1 (en) 2011-09-23 2013-03-28 Qualcomm Incorporated Position estimation via proximate fingerprints
US9137444B2 (en) 2011-09-26 2015-09-15 Sony Corporation Image photography apparatus for clipping an image region
US8617081B2 (en) 2011-09-28 2013-12-31 Xerox Corporation Estimating cardiac pulse recovery from multi-channel source data via constrained source separation
US9020185B2 (en) 2011-09-28 2015-04-28 Xerox Corporation Systems and methods for non-contact heart rate sensing
US8678927B2 (en) 2011-10-04 2014-03-25 Microsoft Corporation Game controller on mobile touch-enabled devices
GB2495325B (en) 2011-10-07 2014-07-16 Irisguard Inc Improvements relating to Iris cameras
TW201315438A (en) 2011-10-14 2013-04-16 Ind Tech Res Inst Method of contact-free heart rate estimation and system thereof
US8600213B2 (en) 2011-10-26 2013-12-03 Xerox Corporation Filtering source video data via independent component selection
US8938282B2 (en) 2011-10-28 2015-01-20 Navigate Surgical Technologies, Inc. Surgical location monitoring system and method with automatic registration
US8235529B1 (en) 2011-11-30 2012-08-07 Google Inc. Unlocking a screen using eye tracking information
US10363102B2 (en) 2011-12-30 2019-07-30 Mako Surgical Corp. Integrated surgery method
EP2626718A1 (en) 2012-02-09 2013-08-14 Koninklijke Philips Electronics N.V. MRI with motion correction using navigators acquired using a Dixon technique
EP2822472B1 (en) 2012-03-07 2022-09-28 Ziteo, Inc. Systems for tracking and guiding sensors and instruments
US9511243B2 (en) 2012-04-12 2016-12-06 University Of Florida Research Foundation, Inc. Prevention of setup errors in radiotherapy
US10925564B2 (en) 2012-04-20 2021-02-23 Siemens Medical Solutions Usa, Inc. Medical imaging system with range imaging-based control
KR101376834B1 (en) 2012-04-27 2014-03-20 가천대학교 산학협력단 a real-time motion tracking of the subject and medical imaging correction method
US9451926B2 (en) 2012-05-09 2016-09-27 University Of Washington Through Its Center For Commercialization Respiratory motion correction with internal-external motion correlation, and associated systems and methods
CN107095678A (en) 2012-05-25 2017-08-29 丹麦科技大学 Apparatus and method for the motion tracking in Brian Imaging
US8971985B2 (en) 2012-06-01 2015-03-03 Xerox Corporation Minute ventilation estimation based on depth maps
US9226691B2 (en) 2012-06-01 2016-01-05 Xerox Corporation Processing a video for tidal chest volume estimation
US8855384B2 (en) 2012-06-20 2014-10-07 Xerox Corporation Continuous cardiac pulse rate estimation from multi-channel source video data
US9036877B2 (en) 2012-06-20 2015-05-19 Xerox Corporation Continuous cardiac pulse rate estimation from multi-channel source video data with mid-point stitching
US8977347B2 (en) 2012-06-25 2015-03-10 Xerox Corporation Video-based estimation of heart rate variability
US8768438B2 (en) 2012-06-25 2014-07-01 Xerox Corporation Determining cardiac arrhythmia from a video of a subject being monitored for cardiac function
US20140005527A1 (en) 2012-06-29 2014-01-02 General Electric Company Method and system for dynamic referencing and registration used with surgical and interventional procedures
AU2013286807A1 (en) 2012-07-03 2015-01-29 The State Of Queensland Acting Through Its Department Of Health Movement correction for medical imaging
US8873812B2 (en) 2012-08-06 2014-10-28 Xerox Corporation Image segmentation using hierarchical unsupervised segmentation and hierarchical classifiers
EP2888601B1 (en) 2012-08-27 2022-01-19 Koninklijke Philips N.V. Motion tracking based on fast image acquisition
WO2014037868A1 (en) 2012-09-06 2014-03-13 Koninklijke Philips N.V. Magnetic resonance imaging system with navigator-based motion detection
DE102012216303A1 (en) 2012-09-13 2014-03-13 Siemens Aktiengesellschaft Magnetic resonance recording unit and a magnetic resonance device with the magnetic resonance recording unit
US9008757B2 (en) 2012-09-26 2015-04-14 Stryker Corporation Navigation system including optical and non-optical sensors
US9084629B1 (en) 2012-10-02 2015-07-21 Scott L Rosa Image guided atlas correction
EP2912484A1 (en) 2012-10-26 2015-09-02 Koninklijke Philips N.V. Reducing interference in a combined system comprising an mri system and a non-mr imaging system
DE102012021623B4 (en) 2012-11-06 2021-03-04 Otto-Von-Guericke-Universität Magdeburg Device and method for calibrating tracking systems in imaging systems
EP2916761A1 (en) 2012-11-06 2015-09-16 Brainlab AG Two-part tracking reference structure
KR101461099B1 (en) 2012-11-09 2014-11-13 삼성전자주식회사 Magnetic resonance imaging apparatus and acquiring method of functional magnetic resonance image using the same
US8792969B2 (en) 2012-11-19 2014-07-29 Xerox Corporation Respiratory function estimation from a 2D monocular video
US20150289878A1 (en) 2012-11-20 2015-10-15 Lacrima Medical, Ltd. Apparatus and methods for applying pressure to a face of a subject
CN103829965B (en) 2012-11-27 2019-03-22 Ge医疗系统环球技术有限公司 The method and apparatus of CT scan is guided using marked body
DE102012222375B3 (en) 2012-12-06 2014-01-30 Siemens Aktiengesellschaft Magnetic coil device for investigation on head of patient, has light field camera element which is provided in camera unit of magnetic coil assembly, such that camera element is arranged within receiving region surrounding shell unit
US10241182B2 (en) 2012-12-12 2019-03-26 Koninklijke Philips N.V. Motion detection and correction method for magnetic resonance diffusion weighted imaging (DWI)
US10591570B2 (en) 2012-12-17 2020-03-17 The Board Of Trustees Of The Leland Stanford Junior University Method for 3D motion tracking in an MRI scanner using inductively coupled microcoils
CN110464301A (en) 2013-01-24 2019-11-19 凯内蒂科尔股份有限公司 For the system, apparatus and method of patient motion to be tracked and compensated during medical image scan
US10327708B2 (en) 2013-01-24 2019-06-25 Kineticor, Inc. Systems, devices, and methods for tracking and compensating for patient motion during a medical imaging scan
US9717461B2 (en) 2013-01-24 2017-08-01 Kineticor, Inc. Systems, devices, and methods for tracking and compensating for patient motion during a medical imaging scan
US9305365B2 (en) 2013-01-24 2016-04-05 Kineticor, Inc. Systems, devices, and methods for tracking moving targets
WO2014120734A1 (en) 2013-02-01 2014-08-07 Kineticor, Inc. Motion tracking system for real time adaptive motion compensation in biomedical imaging
US8862420B2 (en) 2013-02-05 2014-10-14 Reno Sub-Sustems Canada Incorporated Multi-axis tilt sensor for correcting gravitational effects on the measurement of pressure by a capacitance diaphragm gauge
JP6268196B2 (en) 2013-03-05 2018-01-24 コーニンクレッカ フィリップス エヌ ヴェKoninklijke Philips N.V. Consistent continuous ultrasound acquisition for intracranial monitoring
US9395386B2 (en) 2013-03-14 2016-07-19 Dwyer Instruments, Inc. Electronic tilt compensation for diaphragm based pressure sensors
US9629595B2 (en) 2013-03-15 2017-04-25 Hansen Medical, Inc. Systems and methods for localizing, tracking and/or controlling medical instruments
WO2014147519A1 (en) 2013-03-20 2014-09-25 Koninklijke Philips N.V. Neurophysiological monitoring for prospective motion gating in radiological imaging
US8995754B2 (en) 2013-05-30 2015-03-31 Xerox Corporation Estimating a pose of a camera for volume estimation
US9443289B2 (en) 2013-06-21 2016-09-13 Xerox Corporation Compensating for motion induced artifacts in a physiological signal extracted from multiple videos
KR101716421B1 (en) 2013-06-21 2017-03-14 삼성전자주식회사 Method for providing information and medical diagnosis apparatus thereto
RU2015103232A (en) 2013-06-28 2017-08-03 Конинклейке Филипс Н.В. COMPUTER TOMOGRAPHY SYSTEM
US9433386B2 (en) 2013-07-09 2016-09-06 Xerox Corporation Method and apparatus for monitoring a subject for atrial fibrillation
US20160199009A1 (en) 2013-08-10 2016-07-14 Needleways Ltd. Medical needle path display
US10201293B2 (en) 2013-09-11 2019-02-12 Xerox Corporation Non-contact monitoring of spatio-temporal respiratory mechanics via depth sensing
US20150094606A1 (en) 2013-10-02 2015-04-02 Xerox Corporation Breathing pattern identification for respiratory function assessment
CN105555189B (en) 2013-09-17 2020-03-17 小利兰·斯坦福大学托管委员会 Device for obtaining high-quality optical image in nuclear magnetic resonance imaging system
CA2929677C (en) 2013-11-13 2023-10-31 Danmarks Tekniske Universitet Method for surface scanning in medical imaging and related apparatus
WO2015084826A1 (en) 2013-12-02 2015-06-11 The Board Of Trustees Of The Leland Stanford Junior University Determination of the coordinate transformation between an optical motion tracking system and a magnetic resonance imaging scanner
US9504426B2 (en) 2013-12-06 2016-11-29 Xerox Corporation Using an adaptive band-pass filter to compensate for motion induced artifacts in a physiological signal extracted from video
WO2015092593A1 (en) 2013-12-20 2015-06-25 Koninklijke Philips N.V. Optical based subject motion detection in imaging systems
US20150245787A1 (en) 2014-03-03 2015-09-03 Xerox Corporation Real-time video processing for respiratory function analysis
US9336594B2 (en) 2014-03-07 2016-05-10 Xerox Corporation Cardiac pulse rate estimation from source video data
US20150257661A1 (en) 2014-03-11 2015-09-17 Xerox Corporation System and method for determining arterial pulse wave transit time
CN106572810A (en) 2014-03-24 2017-04-19 凯内蒂科尔股份有限公司 Systems, methods, and devices for removing prospective motion correction from medical imaging scans
US9436277B2 (en) 2014-04-21 2016-09-06 Xerox Corporation System and method for producing computer control signals from breath attributes
CN106233154B (en) 2014-04-22 2019-05-31 皇家飞利浦有限公司 Use the magnetic resonance imaging with motion correction of prepulsing and omniselector
EP2944283B1 (en) 2014-05-14 2018-08-15 Stryker European Holdings I, LLC Navigation system for tracking the position of a work target
US9785247B1 (en) 2014-05-14 2017-10-10 Leap Motion, Inc. Systems and methods of tracking moving hands and recognizing gestural interactions
WO2016014718A1 (en) 2014-07-23 2016-01-28 Kineticor, Inc. Systems, devices, and methods for tracking and compensating for patient motion during a medical imaging scan
US10254370B2 (en) 2014-09-25 2019-04-09 The Cleveland Clinic Foundation Modified pulse sequence for magnetic resonance imaging using MRI-visible markers for motion correction
US9693710B2 (en) 2014-10-21 2017-07-04 Xerox Corporation System and method for determining respiration rate from a video
CN107004262B (en) 2014-12-03 2021-05-18 皇家飞利浦有限公司 Digital subtraction angiography system and method based on motion compensation of device
US9986923B2 (en) 2015-01-09 2018-06-05 Xerox Corporation Selecting a region of interest for extracting physiological parameters from a video of a subject
US20160256713A1 (en) 2015-02-11 2016-09-08 Cubresa Inc. Radiation Therapy Guided Using PET Imaging
WO2016172311A1 (en) 2015-04-21 2016-10-27 The Board Of Trustees Of The Leland Stanford Junior University Devices and methods for trackable hearing protection in magnetic resonance imaging
EP3086134A1 (en) 2015-04-22 2016-10-26 Siemens Healthcare GmbH Motion correction in magnetic resonance imaging
US9943247B2 (en) 2015-07-28 2018-04-17 The University Of Hawai'i Systems, devices, and methods for detecting false movements for motion correction during a medical imaging scan
WO2017091479A1 (en) 2015-11-23 2017-06-01 Kineticor, Inc. Systems, devices, and methods for tracking and compensating for patient motion during a medical imaging scan
CN109561853A (en) 2016-04-26 2019-04-02 凯内蒂科尔股份有限公司 The systems, devices and methods of patient motion are tracked and compensated during medical image scan
DE102017201750A1 (en) 2017-02-03 2018-08-09 Siemens Healthcare Gmbh Position determination of an examination object when performing a medical imaging method
KR102382865B1 (en) 2017-06-28 2022-04-05 삼성전자주식회사 Camera Module, Electronic Device including Camera Module

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
D.G. NORRIS; W. DRIESEL, ONLINE MOTION CORRECTION FOR DIFFUSION-WEIGHTED IMAGING USING NAVIGATOR ECHOES: APPLICATION TO RARE IMAGING WITHOUT SENSITIVITY LOSS, vol. 45, 2001, pages 729 - 733
See also references of EP2747641A4

Cited By (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9867549B2 (en) 2006-05-19 2018-01-16 The Queen's Medical Center Motion tracking system for real time adaptive imaging and spectroscopy
US9138175B2 (en) 2006-05-19 2015-09-22 The Queen's Medical Center Motion tracking system for real time adaptive imaging and spectroscopy
US10869611B2 (en) 2006-05-19 2020-12-22 The Queen's Medical Center Motion tracking system for real time adaptive imaging and spectroscopy
US9076212B2 (en) 2006-05-19 2015-07-07 The Queen's Medical Center Motion tracking system for real time adaptive imaging and spectroscopy
US10663553B2 (en) 2011-08-26 2020-05-26 Kineticor, Inc. Methods, systems, and devices for intra-scan motion correction
US9606209B2 (en) 2011-08-26 2017-03-28 Kineticor, Inc. Methods, systems, and devices for intra-scan motion correction
US10327708B2 (en) 2013-01-24 2019-06-25 Kineticor, Inc. Systems, devices, and methods for tracking and compensating for patient motion during a medical imaging scan
US9779502B1 (en) 2013-01-24 2017-10-03 Kineticor, Inc. Systems, devices, and methods for tracking moving targets
US9717461B2 (en) 2013-01-24 2017-08-01 Kineticor, Inc. Systems, devices, and methods for tracking and compensating for patient motion during a medical imaging scan
US9607377B2 (en) 2013-01-24 2017-03-28 Kineticor, Inc. Systems, devices, and methods for tracking moving targets
US10339654B2 (en) 2013-01-24 2019-07-02 Kineticor, Inc. Systems, devices, and methods for tracking moving targets
US9305365B2 (en) 2013-01-24 2016-04-05 Kineticor, Inc. Systems, devices, and methods for tracking moving targets
US9782141B2 (en) 2013-02-01 2017-10-10 Kineticor, Inc. Motion tracking system for real time adaptive motion compensation in biomedical imaging
US10653381B2 (en) 2013-02-01 2020-05-19 Kineticor, Inc. Motion tracking system for real time adaptive motion compensation in biomedical imaging
US10004462B2 (en) 2014-03-24 2018-06-26 Kineticor, Inc. Systems, methods, and devices for removing prospective motion correction from medical imaging scans
US9734589B2 (en) 2014-07-23 2017-08-15 Kineticor, Inc. Systems, devices, and methods for tracking and compensating for patient motion during a medical imaging scan
US10438349B2 (en) 2014-07-23 2019-10-08 Kineticor, Inc. Systems, devices, and methods for tracking and compensating for patient motion during a medical imaging scan
US11100636B2 (en) 2014-07-23 2021-08-24 Kineticor, Inc. Systems, devices, and methods for tracking and compensating for patient motion during a medical imaging scan
US9943247B2 (en) 2015-07-28 2018-04-17 The University Of Hawai'i Systems, devices, and methods for detecting false movements for motion correction during a medical imaging scan
US10660541B2 (en) 2015-07-28 2020-05-26 The University Of Hawai'i Systems, devices, and methods for detecting false movements for motion correction during a medical imaging scan
US10716515B2 (en) 2015-11-23 2020-07-21 Kineticor, Inc. Systems, devices, and methods for tracking and compensating for patient motion during a medical imaging scan
TWI678544B (en) * 2018-02-27 2019-12-01 鴻海精密工業股份有限公司 Magnetic resonance imaging device and dementia monitor system

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US20170276754A1 (en) 2017-09-28

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