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:
May. 18, 2021

Filed:

Jul. 17, 2019
Applicant:

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

Inventors:

Dawei Gui, Sussex, WI (US);

Xiaoli Zhao, New Berlin, WI (US);

Ling Sun, Brookfield, WI (US);

Haonan Wang, Waukesha, WI (US);

Wei Sun, Brookfield, WI (US);

Assignee:

GE PRECISION HEALTHCARE LLC, Milwaukee, WI (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); A61B 6/00 (2006.01); G01R 33/565 (2006.01); G06T 5/00 (2006.01); G06T 7/194 (2017.01); G01R 33/56 (2006.01); G06N 3/08 (2006.01); G01R 33/58 (2006.01);
U.S. Cl.
CPC ...
G01R 33/5659 (2013.01); G01R 33/5608 (2013.01); G01R 33/58 (2013.01); G06N 3/08 (2013.01); G06T 5/002 (2013.01); G06T 5/008 (2013.01); G06T 7/194 (2017.01); G06T 2207/10088 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30004 (2013.01);
Abstract

Methods and systems are provided for predicting Bfield maps from magnetic resonance calibration images using deep neural networks. In an exemplary embodiment a method for magnetic resonance imaging comprises, acquiring a magnetic resonance (MR) calibration image of an anatomical region, mapping the MR calibration image to a transmit field map (Bfield map) with a trained deep neural network, acquiring a diagnostic MR image of the anatomical region, and correcting inhomogeneities of a transmit field in the diagnostic MR image with the Bfield map. Further, methods and systems are provided for collecting and processing training data, as well as utilizing the training data to train a deep learning network to predict Bfield maps from MR calibration images.


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