Abstract: A three-dimensional magnetic resonance image dataset of an object is acquired using a multi-shot imaging protocol in which several k-space lines are acquired in one shot. The three-dimensional k-space includes a central region and a periphery, wherein the sampling order of k-space lines differs between the central region and the periphery. At least one k-space line from each shot passes through the central region, whereas the periphery includes regions, which are sampled by k-space lines from a subset of the plurality of shots.

Abstract: A method for acquiring a magnetic resonance image dataset of an object includes using an imaging protocol in which a number of k-space lines are acquired in one shot. The imaging protocol includes a plurality of shots. A plurality of additional k-space lines are acquired in at least a subset of the shots, such that movement of the object is detected throughout the imaging protocol. A method for generating a motion-corrected magnetic resonance image dataset from the dataset thus acquired, a magnetic resonance imaging apparatus, and a computer program are also provided.

Abstract: A system and method include generation of modified imaging data and modified acquisition parameters of a training example based on the target imaging data and target acquisition parameters of each of a plurality of target examples, and generation, for each training example, of an initial reconstructed image based on the modified imaging data and modified acquisition parameters of the training example. A first network stage of a multi-stage network is trained based on the modified imaging data, modified acquisition parameters and initial reconstructed image of each training example, a first output image is generated for each training example by inputting the modified imaging data, modified acquisition parameters and initial reconstructed image of the training example to the trained first network stage, and a second network stage of the multi-stage network is trained based on the modified imaging data, modified acquisition parameters and first output image of each training example.

Abstract: A method for reconstructing a motion-corrected magnetic resonance image of a subject includes providing k-space magnetic resonance data including a plurality of shots, wherein each shot corresponds to an individual motion state of the subject. The method further includes providing motion parameters related to each motion state, determining redundancies across the motion states of the plurality of shots based on the motion parameters, compressing the plurality of motion states based on the determined redundancies across the motion states, and reconstructing the magnetic resonance image from the k-space magnetic resonance data based on the compressed plurality of motion states.

Abstract: Systems and Methods that identify the effect of motion during a medical imaging procedure. A neural network is trained to translate motion induced deviations of a coil-mixing matrix relative to a reference acquisition into a motion score. This score can be used for the prospective detection of the most corrupted echo trains for removal or triggering a replacement by reacquisition.

Abstract: In a medical imaging auto-calibrated reconstruction method, an imaging scan is performed using a data acquisition scanner to generate image data, calibration data having a uniform sampling is determined, a point-spread function is determined based on the calibration data, and an image is reconstructed from the image data based on the point-spread function. A central region of k-space may have uniform sampling. The calibration data may be determined by extracting a uniformly-sampled central region of k-space from the image data. An outer region of k-space may have non-uniform sampling. A calibration scan may be performed to generate the calibration data.

Abstract: Techniques are disclosed related to the compensation of phase variations introduced into k-space lines, which cause imaging artifacts. The techniques utilize the detection of motion via an encoding plus motion model, which does not require the use of additional prospective or retrospective motion detection techniques. The techniques described herein use the encoding plus motion model to reconstruct an initial image from a set of motion states, and then calculate phase information from images that are projected form the initial reconstructed image using a projection onto convex sets (POCS). The phase information is incorporated into the encoding plus motion model over several iterations to minimize data consistency error, thereby generating a refined image that compensates for patient motion over the set of motion states.

Abstract: Systems and Methods that identify the effect of motion during a medical imaging procedure. A neural network is trained to translate motion induced deviations of a coil-mixing matrix relative to a reference acquisition into a motion score. This score can be used for the prospective detection of the most corrupted echo trains for removal or triggering a replacement by reacquisition.

Abstract: The present disclosure is generally directed to systems and methods for generating de-noised MR images that are reconstructed from a hybridization of two separate image reconstruction pipelines, at least one of which includes the use of a neural network. Further, the amount of influence that the neural network reconstruction has on the hybrid reconstructed image is controlled via a regularization parameter that is selected based on an estimated noise level associated with the initial image acquisition, which can be calculated from pre-scan data.

Abstract: In a method and system for reducing motion artifacts in magnetic resonance image data, a scout scan (e.g. a three-dimensional (3D) scout scan) of the region of the patient is performed, a magnetic resonance (MR) measurement of the region of the patient is performed to acquire two-dimensional (2D) MR image data of the region of the patient, and motion correction is performed on the acquired 2D MR image data based on the scout scan to generate corrected MR image data. The motion correction technique advantageously reduces an influence of a patient motion on the magnetic resonance image data.

Abstract: In a method and system for reducing motion artifacts in magnetic resonance image data, a scout scan (e.g. a three-dimensional (3D) scout scan) of the region of the patient is performed, a magnetic resonance (MR) measurement of the region of the patient is performed to acquire two-dimensional (2D) MR image data of the region of the patient, and motion correction is performed on the acquired 2D MR image data based on the scout scan to generate corrected MR image data. The motion correction technique advantageously reduces an influence of a patient motion on the magnetic resonance image data.

Abstract: A three-dimensional magnetic resonance image dataset of an object is acquired using a multi-shot imaging protocol in which several k-space lines are acquired in one shot. The three-dimensional k-space includes a central region and a periphery, wherein the sampling order of k-space lines differs between the central region and the periphery. At least one k-space line from each shot passes through the central region, whereas the periphery includes regions, which are sampled by k-space lines from a subset of the plurality of shots.

Abstract: A system and method include generation of modified imaging data and modified acquisition parameters of a training example based on the target imaging data and target acquisition parameters of each of a plurality of target examples, and generation, for each training example, of an initial reconstructed image based on the modified imaging data and modified acquisition parameters of the training example. A first network stage of a multi-stage network is trained based on the modified imaging data, modified acquisition parameters and initial reconstructed image of each training example, a first output image is generated for each training example by inputting the modified imaging data, modified acquisition parameters and initial reconstructed image of the training example to the trained first network stage, and a second network stage of the multi-stage network is trained based on the modified imaging data, modified acquisition parameters and first output image of each training example.

Abstract: Techniques are disclosed related to the compensation of phase variations introduced into k-space lines, which cause imaging artifacts. The techniques utilize the detection of motion via an encoding plus motion model, which does not require the use of additional prospective or retrospective motion detection techniques. The techniques described herein use the encoding plus motion model to reconstruct an initial image from a set of motion states, and then calculate phase information from images that are projected form the initial reconstructed image using a projection onto convex sets (POCS). The phase information is incorporated into the encoding plus motion model over several iterations to minimize data consistency error, thereby generating a refined image that compensates for patient motion over the set of motion states.

Abstract: In a medical imaging auto-calibrated reconstruction method, an imaging scan is performed using a data acquisition scanner to generate image data, calibration data having a uniform sampling is determined, a point-spread function is determined based on the calibration data, and an image is reconstructed from the image data based on the point-spread function. A central region of k-space may have uniform sampling. The calibration data may be determined by extracting a uniformly-sampled central region of k-space from the image data. An outer region of k-space may have non-uniform sampling. A calibration scan may be performed to generate the calibration data.

Abstract: In a method and system for reducing motion artifacts in magnetic resonance image data, a scout scan of the region of the patient is performed, a magnetic resonance (MR) measurement of the region of the patient is performed to acquire MR image data of the region of the patient, and motion correction is performed on the acquired MR image data based on the scout scan to generate corrected MR image data. The motion correction technique advantageously reduces an influence of a patient motion on the magnetic resonance image data.

Abstract: The disclosure relates to a computer implemented method for magnetic resonance imaging. The method includes: receiving at least a first and a second subset of k-space data as radio frequency signals emitted from excited hydrogen atoms of a subject; sampling the first and second subset of k-space data; choosing the first subset of k-space data as a base subset of k-space data; estimating motion parameters of the second subset of k-space data against the base subset of k-space data; and correcting the second subset of k-space data based on the estimated motion parameters of the second subset of k-space data. The motion parameters of the second subset of k-space data are parameters of a non-linear motion estimating function representing a motion of the subject between receiving the first subset of k-space data and receiving the second subset of k-space data.

Abstract: The disclosure relates to a computer implemented method for magnetic resonance imaging. The method includes: receiving at least a first and a second subset of k-space data as radio frequency signals emitted from excited hydrogen atoms of a subject; sampling the first and second subset of k-space data; choosing the first subset of k-space data as a base subset of k-space data; estimating motion parameters of the second subset of k-space data against the base subset of k-space data; and correcting the second subset of k-space data based on the estimated motion parameters of the second subset of k-space data. The motion parameters of the second subset of k-space data are parameters of a non-linear motion estimating function representing a motion of the subject between receiving the first subset of k-space data and receiving the second subset of k-space data.

Abstract: A method for accelerated segmented magnetic resonance (MR) image data acquisition includes using a plurality of RF pulses to excite one or more slices of an anatomical area of interest according to a predetermined slice acceleration factor. Next, a collapsed image comprising the slices is acquired using a consecutive segment acquisition process. Then, a parallel image reconstruction method is applied to the collapsed image to separate the collapsed image into a plurality of slice images.

Abstract: A magnetic resonance (MR) method and system are provided for generating real-time prospective motion-corrected images using fast navigators. The real-time motion correction is achieved by using a 2D EPI navigator that is obtained using a simultaneous multi-slice blipped-CAIPI technique. The navigator parameters such as field of view, voxel size, and matrix size can be selected to facilitate fast acquisition while providing information sufficient to detect rotational motions on the order of several degrees or more and translational motions on the order of several millimeters or more. The total time interval for obtaining and reconstructing navigator data, registering the navigator image, and providing feedback to correct for detected motion, can be on the order of about 100 ms or less. This prospective motion correction can be used with a wide range of MR imaging techniques where the pulse sequences do not have significant intervals of “dead” time.