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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.

Patent No.:

US 12494042 B1

PDFFull Text
Date of Patent:
Dec. 09, 2025

Filed:

Jun. 06, 2023

Image processing method, image processing system, and non-transitory computer readable medium

Applicant:

Canon Medical Systems Corporation, Tochigi, JP;

Inventors:

Sha Wang, Beijing, CN;

Bing Han, Beijing, CN;

Fanjie Meng, Beijing, CN;

Qiqi Xu, Beijing, CN;

Ye Yue, Beijing, CN;

Assignee:

CANON MEDICAL SYSTEMS CORPORATION, Tochigi, JP;

Attorney:

Oblon, McClelland, Maier & Neustadt, L.L.P.

Primary Examiner:

Henok Shiferaw

Assistant Examiner:

Dennis undefined Rosario

Int. Cl.
CPC ...
G06V 10/764 (2022.01); A61B 5/00 (2006.01); G06F 9/455 (2018.01); G06F 18/25 (2023.01); G06N 3/02 (2006.01); G06N 5/04 (2023.01); G06N 5/045 (2023.01); G06N 5/046 (2023.01); G06N 20/00 (2019.01); G06N 20/20 (2019.01); G06T 5/60 (2024.01); G06T 7/10 (2017.01); G06T 7/11 (2017.01); G06T 7/12 (2017.01); G06V 10/25 (2022.01); G06V 10/26 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06V 20/69 (2022.01); G16H 50/30 (2018.01);
U.S. Cl.
CPC ...
G06V 10/764 (2022.01); A61B 5/7267 (2013.01); G06F 18/25 (2023.01); G06N 3/02 (2013.01); G06N 5/04 (2013.01); G06N 5/042 (2013.01); G06N 5/045 (2013.01); G06N 5/046 (2013.01); G06N 20/00 (2019.01); G06N 20/20 (2019.01); G06T 5/60 (2024.01); G06T 7/10 (2017.01); G06T 7/11 (2017.01); G06T 7/12 (2017.01); G06V 10/25 (2022.01); G06V 10/26 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06V 20/695 (2022.01); G16H 50/30 (2018.01); G06F 2009/4557 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20112 (2013.01); G06T 2207/20128 (2013.01); G06T 2207/20152 (2013.01); G06T 2207/30004 (2013.01); G06T 2207/30056 (2013.01); G06V 2201/03 (2022.01);
Abstract

An image processing method according to an embodiment includes a specifying step, an inference step, and an integration step. In the specifying step, a first portion including a region corresponding to an anatomical site of a target and a second portion including a region different from the anatomical site are specified in the image. In the inference step, by using a deep learning model, segmentation of the region corresponding to the anatomical site is performed on the first portion and segmentation of the region different from the anatomical site is performed on the second portion, or classification and detection of an image including the region corresponding to the anatomical site is performed on the first portion and classification and detection of an image including the region different from the anatomical site is performed on the second portion. In the integration step, results of the respective processes are integrated for output.

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