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:
Sep. 21, 2021

Filed:

Oct. 11, 2017
Applicants:

General Electric Company, Schenectady, NY (US);

Purdue University, West Lafayette, IN (US);

Notre Dame University, Notre Dame, IN (US);

Inventors:

Jean-Baptiste Thibault, Waukesha, WI (US);

Somesh Srivastava, Waukesha, WI (US);

Jiang Hsieh, Brookfield, WI (US);

Charles A. Bouman, Jr., West Lafayette, IN (US);

Dong Ye, West Lafayette, IN (US);

Ken Sauer, Notre Dame, IN (US);

Assignees:

GENERAL ELECTRIC COMPANY, Schenectady, NY (US);

PURDUE UNIVERSITY, West Lafayette, IN (US);

NOTRE DAME UNIVERSITY, Notre Dame, IN (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2006.01); G06T 11/00 (2006.01); G01N 23/046 (2018.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G01N 23/046 (2013.01); G06N 20/00 (2019.01); G06T 11/003 (2013.01); G06T 11/008 (2013.01); G01N 2223/419 (2013.01); G06T 2207/10072 (2013.01); G06T 2207/20084 (2013.01); G06T 2211/421 (2013.01); G06T 2211/424 (2013.01);
Abstract

The present approach relates to the training of a machine learning algorithm for image generation and use of such a trained algorithm for image generation. Training the machine learning algorithm may involve using multiple images produced from a single set of tomographic projection or image data (such as a simple reconstruction and a computationally intensive reconstruction), where one image is the target image that exhibits the desired characteristics for the final result. The trained machine learning algorithm may be used to generate a final image corresponding to a computationally intensive algorithm from an input image generated using a less computationally intensive algorithm.


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