Canon Medical Systems Corporation

Toshiba Medical Systems Corporation

Kabushiki Kaisha Toshiba

Koninklijke Philips Corporation N.v.

Andrew James Wheaton

Wayne R Dannels

Anuj Sharma

Samir Dev Sharma

Antonios Matakos

Michael R Thompson

Mitsue Miyazaki

Joseph Manak

James B Murdoch

Deepak V Bhat

Ad L Moerland

Bradley Stephens

A method for determining an intensity-corrected magnetic resonance image includes acquiring B1 projection data of a patient using a magnetic resonance imaging system. The method also includes determining a transmit map using only the acquired B1 projection data. The method further includes acquiring an image of a patient using magnetic resonance imaging system and correcting an image intensity of the acquired image using the determined set of maps. The method also includes outputting the corrected image of the patient.

Method for fast TX/RX intensity correction calibration using B1 projections in magnetic resonance imaging systems

A method and system for modifying a series of magnetic resonance imaging (MRI) scan sequences for use in a single MRI examination. In one embodiment, a method and system intersperse a set of B1 amplitude measurement sequences within a received series of MRI scan sequences such that an RF parameter value of at least one scan sequence of the received series of MRI scan sequences is altered based on the results of at least one of the interspersed set of B1 amplitude measurement sequences.

Magnetic resonance imaging method, system, and computer program product utilizing B1 amplitude-based corrections

An apparatus for magnetic resonance imaging includes processing circuitry to obtain a set of sequence instructions for performing a magnetic resonance scan; partition the obtained set of sequence instructions into a plurality of kernels by determining partition time points defining boundaries of the plurality of kernels, wherein the partition time points are not equally spaced in time; convert a first kernel of the plurality of kernels into a first hardware instruction set; transmit the first hardware instruction set to a hardware board controller for execution; and reconstruct a magnetic resonance image from received data, including data obtained by executing the first kernel.

Backend sequence kernel

An apparatus for incremental motion correction in medical imaging. The apparatus for motion correction in magnetic resonance imaging includes processing circuitry configured to estimate an intermediate image from a first section of k-space, the first section of the k-space corresponding to acquisition time points within a magnetic resonance scan of a subject, the corresponding acquisition time points within the magnetic resonance scan being associated with shots of the k-space determined to have minimal motion, estimate motion parameters of a second section of the k-space using the estimated intermediate image, combine data from the first section of the k-space with data from the second section of the k-space according to the estimated motion parameters, and reconstruct the combined data of the k-space to generate a final image.

System, apparatus, and method for incremental motion correction in magnetic resonance imaging

An apparatus and method are provided to simultaneously provide good image quality and fast image reconstruction from magnetic resonance imaging (MRI) data by selecting an appropriate value for the regularization parameter used in compressed sensing (CS) image reconstruction. In CS reconstruction a high-resolution image can be reconstructed from randomized undersampled data by imposing sparsity in multi-scale transformation (e.g., wavelet) domain. Further, in the transformation domain, a threshold can be determined between signal and noise levels of the transform coefficients. A regularization parameter based on this threshold scales the regularization term, which imposes sparsity, relative to the data fidelity term in an objective function, thereby balancing the tradeoff between noise and smoothing.

Method and apparatus for automated regularization tuning in magnetic resonance imaging (MRI) using compressed sensing (CS)

A method and apparatus are provided to perform controlled aliasing in parallel imaging (CAIPI) using time shifts between the radio frequency (RF) excitation pulses and the waveform of the slice-select gradient field to shift respective sampling points within the two-dimensions of k-space corresponding to phase encoding. Thus, a CAIPI sampling pattern is generated using time shifts, rather than by modulating the RF excitation pulses or gradient fields.

Apparatus and method using time shifts in magnetic resonance imaging (MRI) to implement controlled aliasing in parallel imaging (CAIPI)

A magnetic resonance imaging system includes an array radiofrequency coil and processing circuitry operatively linked to the array radiofrequency coil and configured to receive output signals from the array radiofrequency coil commensurate with a simultaneous multi-slice magnetic imaging characterized by simultaneous multi-slice parameters, estimate distorted regions of the image volume using either data obtained via a pre-scan or a pre-computed model, minimize overlap of the distorted regions with image voxels representing tissue to obtain optimized values of the simultaneous multi-slice parameters, configuring and executing the simultaneous multi-slice imaging sequence based on the optimized values of the simultaneous multi-slice parameters, and reconstruct simultaneous multi-slice images with minimized artifacts.

Systems and methods for image artifact reduction in simultaneous multi-slice magnetic resonance imaging

An apparatus and method of detecting a characteristic in an image is performed by obtaining, from an image capturing apparatus, raw signal data formed from a plurality of data samples and including a signal of interest captured by the image capturing apparatus and classifying, using a neural network, samples other than the signal of interest using a classifier having been determined using a first parameter based on information about the sample and a second parameter based on information identifying a position of the sample within the raw image data.

Apparatus, system and method for machine learning spike noise detection

An apparatus and method are provided to correct motion artifacts in magnetic resonance imaging (MRI) data by finding and removing motion-corrupted encodes. The MRI data non-uniformly sample k-space using a series of shots, each including one or more encodes. The motion-corrupted encodes/shots are identified by omitting respective encodes/shots from the MRI data when reconstructing respective images using a compressed-sensing (CS) method. The image quality is improved for those reconstructed images in which the motion-corrupted encodes are omitted, whereas all other images include the motion-corrupted encodes and exhibit the motion artifact. Assuming a minority of encodes/shots are corrupted by motion, the images improved by omitting the motion-corrupted encodes can be identified as outliers. Once, the motion-corrupted encodes are identified and excluded from the final MRI dataset, a final, high-resolution image is reconstructed using the final MRI dataset.

Method and apparatus for adaptive compressed sensing (CS) to correct motion artifacts in magnetic resonance imaging (MRI)

An apparatus and method are provided to correct motion artifacts in magnetic resonance imaging (MRI) data by obtaining magnetic resonance imaging (MRI) data, the MRI data including imaging segments and corresponding navigator segments, each imaging segment sampled over a respective regions of two or more regions of a k-space grid, one of the navigator segments being selected as a reference navigator segment; generating, for each imaging segment of the imaging segments, a respective phase map based on the reference navigator segment and a corresponding navigator segment of the each imaging segment; applying the respective phase maps to the corresponding imaging segments to generate corrected imaging segments; averaging the corrected imaging segments in k-space to generate averaged imaging segments; and reconstructing an MRI image based on the averaged imaging segments.

Readout-segmented echo planar imaging with k-space averaging

Devices, systems, and methods for generating a medical image receive scan data, wherein the scan data is defined in an acquisition space; perform a first reconstruction process to generate a lower-resolution image based on the scan data, wherein the first reconstruction process uses a subset of the scan data; and perform a second reconstruction process to generate a higher-resolution image based on the scan data, wherein the second reconstruction process uses more of the scan data than the subset of the scan data.

Devices, systems, and methods for medical imaging

An MRI system includes processing circuitry configured to generate two or more RF pulses to form a spin echo, wherein each RF pulse corresponds to selecting at least two slice locations. Additionally, the MRI system encodes magnetic resonance (MR) magnetization to form echo signal data for each RF pulse, applies a set of time-shifts to a slice-selection gradient for each selected slice location, generates a pattern of slice-position-dependent moments on the echo signal data based on the set of time-shifts to the slice-selection gradient, receives image data corresponding to the echo signal data, and reconstructs the image data to form a plurality of images, wherein each of the plurality of images corresponds to one of the selected slice locations.

Systems, methods, and computer-readable storage medium for magnetic resonance imaging

Magnetic resonance imaging (MRI) systems and methods to effect MRI data acquisition with reduced noise in fast spin echo (FSE) and spin echo (SE) implementations are described. The improved MRI data acquisition is performed by acquiring k-space data while maintaining a constant or near constant slice select gradient amplitude throughout a sequence kernel. The acquired k-space data can then be used to generate an MR image.

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Shaker Heights, OH, United States of America

Andrew James Wheaton