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:
Jul. 23, 2024

Filed:

Dec. 22, 2020
Applicant:

GE Precision Healthcare Llc, Wauwatosa, WI (US);

Inventors:

Daniel Vance Litwiller, Denver, CO (US);

Robert Marc Lebel, Calgary, CA;

Xinzeng Wang, Houston, TX (US);

Arnaud Guidon, Somerville, MA (US);

Ersin Bayram, Houston, TX (US);

Assignee:

GE Precision Healthcare LLC, Wauwatosa, WI (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 11/00 (2006.01); A61B 5/00 (2006.01); A61B 5/055 (2006.01); G01R 33/56 (2006.01); G01R 33/565 (2006.01); G06T 7/00 (2017.01);
U.S. Cl.
CPC ...
G06T 11/008 (2013.01); A61B 5/055 (2013.01); A61B 5/7203 (2013.01); A61B 5/7267 (2013.01); G01R 33/5608 (2013.01); G01R 33/565 (2013.01); G06T 7/0012 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30004 (2013.01);
Abstract

A computer-implemented method of removing truncation artifacts in magnetic resonance (MR) images is provided. The method includes receiving a crude image that is based on partial k-space data from a partial k-space that is asymmetrically truncated in at least one k-space dimension. The method also includes analyzing the crude image using a neural network model trained with a pair of pristine images and corrupted images. The corrupted images are based on partial k-space data from partial k-spaces truncated in one or more partial sampling patterns. The pristine images are based on full k-space data corresponding to the partial k-space data of the corrupted images, and target output images of the neural network model are the pristine images. The method further includes deriving an improved image of the crude image based on the analysis, wherein the derived improved image includes reduced truncation artifacts and increased high spatial frequency data.


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