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:
Nov. 14, 2023

Filed:

Nov. 18, 2020
Applicant:

Canon Medical Systems Corporation, Tochigi, JP;

Inventors:

Qiulin Tang, Buffalo Grove, IL (US);

Jian Zhou, Buffalo Grove, IL (US);

Zhou Yu, Glenview, IL (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01); G06N 3/08 (2023.01); G06T 7/12 (2017.01); G06T 11/00 (2006.01); A61B 6/03 (2006.01); A61B 6/00 (2006.01); G16H 50/50 (2018.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); A61B 6/032 (2013.01); A61B 6/504 (2013.01); A61B 6/5264 (2013.01); G06N 3/08 (2013.01); G06T 7/12 (2017.01); G06T 11/005 (2013.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01); G16H 50/70 (2018.01); G06T 2207/10081 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30101 (2013.01); G06T 2211/436 (2013.01);
Abstract

Devices, systems, and methods obtain scan data that were generated by scanning a scanned region, wherein the scan data include groups of scan data that were captured at respective angles; generate partial reconstructions of at least a part of the scanned region, wherein each partial reconstruction of the partial reconstructions is generated based on a respective one or more groups of the groups of scan data, and wherein a collective scanning range of the respective one or more groups is less than the angular scanning range; input the partial reconstructions into a machine-learning model, which generates one or more motion-compensated reconstructions of the at least part of the scanned region based on the partial reconstructions; calculate a respective edge entropy of each of the one or more motion-compensated reconstructions of the at least part of the scanned region; and adjust the machine-learning model based on the respective edge entropies.


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