University of Utah Research Foundation

Siemens Healthcare Gmbh

Ganesh Sharma Adluru Venkata Raja

Bradley Drake Bolster, Jr

Edward V R DiBella

Edward DiBella

A method for reducing artifacts in magnetic resonance imaging (MRI) data includes acquiring a k-space dataset of an anatomical subject using a MRI scanner. An iterative compressed sensing reconstruction method is used to generate a reconstructed image based on the k-space dataset. This iterative compressed sensing reconstruction method uses (a) L1-norm based total variation constraints applied the temporal and spatial dimensions of the k-space dataset and (b) a low rank constraint. After the reconstructed image is generated, a deep learning network is used to generate an artifact image depicting motion artifacts present in the reconstructed image. The reconstructed image is subtracted from the artifact image to yield a final image with the motion artifacts removed.

Deep learning reconstruction of free breathing perfusion

A method, system, and computer-readable medium are provided which perform reconstruction of an image from undersampled, multi-image k-space data. A first undersampled image dataset and a second undersampled image dataset defined in a first dimension are received. The first undersampled image dataset and the second undersampled image dataset define a multi-image dimension. An ordering for a plurality of pixels of the first dimension in the multi-image dimension is defined. The first undersampled image dataset and the second undersampled image dataset in the multi-image dimension are sorted based on the defined ordering. A first constraint is defined in the first dimension using the unsorted first and second undersampled image datasets. A second constraint is defined in the multi-image dimension using the sorted first and second undersampled image datasets. An image is reconstructed using the applied first constraint and the applied second constraint while preserving fidelity to the first undersampled image dataset and the second undersampled image dataset.

Growing community of inventors

Salt Lake City, UT, United States of America

Ganesh Sharma Adluru Venkata Raja