University of California

Siemens Healthineers Ag

Peng Hu

Da Wang

Stanislas Rapacchi

Xiaodong Zhong

Chang Gao

J Paul Finn

Fei Han

Valid Ghodrati

Systems and methods for generative adversarial networks (GANs) to remove artifacts from undersampled magnetic resonance (MR) images are described. The process of training the GAN can include providing undersampled 3D MR images to the generator model, providing the generated example and a real example to the discriminator model, applying adversarial loss, L2 loss, and structural similarity index measure loss to the generator model based on a classification output by the discriminator model, and repeating until the generator model has been trained to remove the artifacts from the undersampled 3D MR images. At runtime, the trained generator model of the GAN can be generate artifact-free images or parameter maps from undersampled MRI data of a patient.

Method and system for accelerated acquisition and artifact reduction of undersampled MRI using a deep learning based 3D generative adversarial network

A system and method is provided for acquiring flow encoded data from a subject using a magnetic resonance imaging (MRI) system. The method includes acquiring flow encoded (FE) data with alternating encoding polarities and along two of three orthogonal directions through the subject over at least two cycles of the flow within the subject; and separating the FE data into directional FE datasets using a temporal filter that separates the FE data based on temporal modulation of the FE directions caused by the alternating encoding polarities extending over the at least two cycles of the flow within the subject that shift the Fourier spectrum of velocity waveforms corresponding to the FE data. The method also includes using the directional FE datasets to generate an image of the subject showing flow within the subject caused by the at least two cycles of flow within the subject.

System and method for phase-contrast MRI with hybrid one- and two-sided flow-encoding and velocity spectrum separation (HOTSPA)

Disclosed herein are methods and systems for clinical practice of medical imaging on patients with metal-containing devices, such as implanted cardiac devices. In particular, Disclosed herein are methods and systems for improved late gadolinium enhancement (LGE) MRI for assessing myocardial viability for patients with implanted cardiac devices, i.e., cardiac pacemakers and implantable cardiac defibrillators.

Cardiac late gadolinium enhancement MRI for patients with implanted cardiac devices

A method for high spatial and temporal resolution dynamic contrast enhanced magnetic resonance imaging using a random subsampled Cartesian k-space using a Poisson-disk random pattern acquisition strategy and a compressed sensing reconstruction algorithm incorporating magnitude image subtraction is presented. One reconstruction uses a split-Bregman minimization of the sum of the L1 norm of the pixel-wise magnitude difference between two successive temporal frames, a fidelity term and a total variation (TV) sparsity term.

High spatial and temporal resolution dynamic contrast-enhanced magnetic resonance imaging

System and method for phase-contrast MRI with hybrid one-and two-sided flow encoding and velocity spectrum separation (HOTSPA)

A phase-contrast MRI (PC-MRI) system and method employing a Hybrid One- and Two-sided Flow Encoding Only (HOTFEO) acquisition scheme for accurate blood flow and velocity measurements of three-directional-velocity-encoding PC-MRI.

Hybrid one- and two-sided flow-encoding only (HOTFEO) for velocity-encoding phase contrast MRI

3D cine MR angiography systems and methods are disclosed for use during the steady state intravascular distribution phase of ferumoxytol. The 3D cine MRA technique enables improved delineation of cardiac anatomy in pediatric patients undergoing cardiovascular MRI.

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Los Angeles, CA, United States of America

Peng Hu