The General Hospital Corporation

Siemens Healthcare Gmbh

Case Western Reserve University

Siemens Aktiengesellschaft

Massachusetts Institute of Technology

Siemens Healthineers Ag

National Institutes of Health, a Component of the US Dept. of Health & Human Services

The Brigham and Women's Hospital, Inc.

Kawin Setsompop

Lawrence Leroy Wald

Stephen Farman Cauley

Daniel Polak

Jonathan R Polimeni

Berkin Bilgic

Elfar Adalsteinsson

Mark A Griswold

Thomas Witzel

Fuyixue Wang

Hua Guo

Yun Jiang

Vijayanand Alagappan

Jason Stockmann

Timothy G Reese

Borjan Aleksandar Gagoski

Huihui Ye

Zijing Dong

Cornelius Eichner

Hans-Peter Fautz

Himanshu Bhat

Vikas Gulani

Dan Ma

William Allyn Grissom

Esther Raithel

Daniel Nicolas Splitthoff

Joerg Ulrich Fontius

Vivek K Goyal

Keith Aaron Heberlein

Jinmin Xu

William Scott Hoge

Adam C Zelinski

Alice Yang

Yogesh Rathi

Bo Zhao

Adam Charles Zelinski

Lawrence L Waid

Avery J L Berman

Merlin John Casper Fair

Lipeng Ning

Sohyun Han

Oleg Michailovich

Magnetic resonance imaging ('MRI') using a PROPELLER echo-planar time-resolved imaging with dynamic encoding (“PEPTIDE”) scheme is described. The PEPTIDE scheme combines a PROPELLER-style trajectory with an echo-planar time-resolved imaging (“EPTI”) acquisition framework, along with dynamic-updating of sensitivity-encoding information.

Propeller echo planar time-resolved imaging with dynamic encoding

Lipid suppression in magnetic resonance imaging ('MRI') is provided on a slice-by-slice basis using tailored local field control that is configured for lipid control for each slice in a planned slice prescription. Only those lipid voxels that fall within the bandwidth of the concurrent RF excitation pulse are targeted. Switched Boffset fields are used to improve lipid suppression pulse performance by pushing water and lipids apart in the frequency domain. Multi-coil Bshim arrays with rapidly switchable output currents that can be turned on during the lipid suppression pulse may be used. A convex optimization may be used to jointly solve for the shim currents and the lipid suppression pulse center frequency and bandwidth to optimize lipid suppression while minimizing water signal loss.

Lipid suppression in magnetic resonance imaging using multi-coil local Bfield control

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.

Scout acquisition enables rapid motion estimation and reduction (SAMER) systems and methods for retrospective motion mitigation

A method for reconstructing a MRI image may include: receiving MRI measurement data sets fto f, each data set being acquired from an examination object based on a different MRI protocol of an MRI system; receiving MRI images uto ucorresponding to the MRI measurement data sets fto f; performing one or more translation and rotation transformations on the MRI images uto u; applying one or more trained functions: to the transformed MRI images uto u, using a neural network, and to the MRI images uto u, using a forward-sampling operator; performing one or more inverse translation and rotation transformations on an output of the neural network; and generating at least one output MRI image ubased on an output of the forward-sampling operator, the inversely transformed output of the neural network, and the input MRI images uto u.

Multi-contrast MRI image reconstruction using machine learning

Described here are systems and methods for producing images with a magnetic resonance imaging ('MRI') system using a high-resolution, motion-robust, artifact-free segmented echo planar imaging (“EPI”) technique. In particular, a fast low angle excitation echo planar imaging technique (“FLEET”) using variable flip angle (“VFA”) radio frequency (“RF”) excitation pulses that are recursively designed to have a flat magnitude and phase profile across a slice for a range of different flip angles by accounting for longitudinal magnetization remaining after each preceding RF pulse is applied.

Multi-shot echo planar imaging using reordered segments and recursive radio frequency pulse design giving matched slice profiles across segments

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.

Phase estimation for retrospective motion correction

Systems and methods are provided for improving MRI data acquisition efficiency while providing more detailed information with high resolution and isotropic resolution without gaps. Improved data acquisition efficiency may be achieved by implementing a machine learning algorithm with a hardware processor and a memory to estimate imperfections in fast imaging sequences, such as a multi-shot echo planar imaging (MS-EPI) sequence. These imperfections, such as patient motion, physiological noise, and phase variations, may be difficult to model or otherwise estimate using standard physics-based reconstructions.

Multi-shot echo planar imaging through machine learning

A method includes determining an initial magnetic resonance imaging, MRI, dataset () in image domain based on an initial reconstruction of MRI measurement data obtained using an undersampling scheme (); and determining patches (-) of the initial MRI dataset () in accordance with a patching scheme, the patching scheme depending on the undersampling scheme (); and, for each one of the patches (-): applying a machine-learned algorithm to obtain a respective patch (-) of a reconstructed MRI dataset, the machine-learned algorithm depending on the undersampling scheme (); and combining the patches (-) of the reconstructed MRI dataset.

Reconstruction of magnetic-resonance datasets using machine learning

Techniques are disclosed related to the compensation of phase offsets introduced into k-space lines as a result of encoding of blip gradients due when motion is present, which may be used for parallel magnetic resonance imaging (MRI) techniques such as blipped SMS or blipped CAIPIRINHA. The compensation of these additional phase offsets may prevent artifacts that would otherwise be present in the reconstructed images as a result of motion during the MRI scanning procedure. The additional phase offsets may be accounted for during the image acquisition phase of the MRI scan or, alternatively, during the image reconstruction phase.

Motion corrected blipped CAIPIRINHA and SMS

A computer-implemented method for reconstructing a MRI image, including: receiving a plurality of MRI measurement data sets &#x192;to &#x192;, wherein each data set is acquired from an examination object based on a different MRI protocol of an MRI system; receiving MRI images uto ucorresponding to the MRI measurement data sets &#x192;to &#x192;; applying, in at least a first step GD, trained functions to the MRI images uto u, using a neural network and a forward-sampling operator, wherein at least one output MRI image uis generated; and providing the at least one output MRI image u, wherein the forward-sampling operator determines an agreement between at least one MRI image uto uand the corresponding MRI measurement data set &#x192;to &#x192;.

Described here are systems and methods for producing images of a subject using magnetic resonance imaging ('MRI') in which data are acquired using a sparse approximate encoding scheme for controlled aliasing techniques. As one example, the sparse approximate encoding can be used for a Wave-CAIPI encoding scheme, which can enable faster image reconstruction using fewer computational resources, in addition to reducing noise in the reconstructed images relative to those reconstructed from data acquired using a Wave-CAIPI encoding scheme without sparse approximate encoding.

Sparse approximate encoding of Wave-CAIPI: preconditioner and noise reduction

Systems and methods for magnetic resonance imaging ('MRI') that address the geometric distortions and blurring common to conventional echo planar imaging ('EPI') sequences, and that provide new temporal signal evolution information across the EPI readout, are described. Echo planar time-resolved imaging (&#x201c;EPTI&#x201d;) schemes are described to implement an accelerated sampling of a hybrid space spanned by the phase encoding dimension and the temporal dimension. In general, each EPTI shot covers a segment of this hybrid space using a zigzag trajectory with an interleaved acceleration in the phase-encoding direction. The hybrid space may be undersampled and a tilted reconstruction kernel used to synthesize additional data samples.

Method for echo planar time-resolved magnetic resonance imaging

Methods for reducing scan time in magnetic resonance imaging ('MRI'), particularly when imaging three-dimensional image volumes, using a simultaneous time-interleaved multislice ('STIMS') acquisition are described. The unused time in each repetition time (&#x201c;TR&#x201d;) period is exploited to provide an additional reduction in encoding time for a three-dimensional acquisition (e.g., a 3D whole brain coverage). Groups of spatially interleaved slices are excited in a single TR, with the excitation and acquisition of the groups of slices being interleaved in time.

Method for simultaneous time-interleaved multislice magnetic resonance imaging

Systems and methods for simultaneously acquiring high-resolution images of a subject from multiple different slice locations using magnetic resonance imaging ('MRI') are described. The present invention overcomes the aforementioned drawbacks by providing method for producing a plurality of images of a subject with a magnetic resonance imaging ('MRI') system. A radio frequency (RF) excitation field is applied by the MRI system to a portion of a subject that includes a plurality of slice locations. First data are simultaneously acquired from each of the plurality of slice locations by the MRI system.

Systems and methods for slice dithered enhanced resolution simultaneous multislice magnetic resonance imaging

Systems and methods for accelerated diffusion-weighted magnetic resonance imaging using a tilted reconstruction kernel to synthesize unsampled k-space data in phase encoded and point spread function ('PSF') encoded k-space data are provided. Images reconstructed from the data have reduced B-related distortions and reduced T* blurring. In general, data are acquired with systematically optimized undersampling of the PSF and phase encoding subspace. Parallel imaging reconstruction is implemented with a Binhomogeneity informed approach to achieve greater than twenty-fold acceleration of the PSF encoding dimension. A tilted reconstruction kernel is used to exploit the correlations in the phase encoding-PSF encoding subspace. Self-navigated phase corrections are computed from the acquired data and used to synthesize the unsampled k-space data.

Accelerated diffusion-weighted magnetic resonance imaging with self-navigated, phase corrected tilted kernel reconstruction of phase encoded and point spread function encoded k-space

Growing community of inventors

Charlestown, MA, United States of America

Kawin Setsompop