The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 29, 2015

Filed:

Feb. 06, 2014
Applicant:

University of Virginia Patent Foundation, Charlottesville, VA (US);

Inventors:

Frederick H Epstein, Charlottesville, VA (US);

Xiao Chen, Charlottesville, VA (US);

Yang Yang, Charlottesville, VA (US);

Michael Salerno, Charlottesville, VA (US);

Assignee:

University of Virginia Patent Foundation, Charlottesville, VA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/20 (2006.01); G06T 7/00 (2006.01); G06K 9/62 (2006.01); G01R 33/565 (2006.01); G01R 33/563 (2006.01); G01R 33/56 (2006.01); G01R 33/561 (2006.01);
U.S. Cl.
CPC ...
G06T 7/20 (2013.01); G01R 33/56308 (2013.01); G01R 33/56509 (2013.01); G06K 9/6218 (2013.01); G06T 7/0012 (2013.01); G01R 33/561 (2013.01); G01R 33/5608 (2013.01); G06K 2209/05 (2013.01); G06T 2207/10096 (2013.01); G06T 2207/30048 (2013.01);
Abstract

Some aspects of the present disclosure relate to systems and methods for accelerated dynamic magnetic resonance imaging (MRI). In an example embodiment, a method includes acquiring undersampled MRI data corresponding to a set of images associated with an area of interest of a subject, and separating an image of the set of images into image regions. The method also includes performing motion tracking for each of the image regions, grouping the motion-tracked image regions into clusters, and applying a sparsity transform to the clusters, to form sparsity-exploited, transformed image regions. The method further includes forming a set of merged images from the plurality of sparsity-exploited, transformed image regions, and updating the set of merged images based on data fidelity, to form an updated set of estimated images.


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