IDiyas

For the Inventor, By the Inventor

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 11961226 B1

PDFFull Text
Date of Patent:
Apr. 16, 2024

Filed:

Oct. 23, 2020

Medical image recognition method, model training method, and computer device

Applicant:

Tencent Technology (Shenzhen) Company Limited, Guangdong, CN;

Inventors:

Kaiwen Xiao, Shenzhen, CN;

Zhongqian Sun, Shenzhen, CN;

Chen Cheng, Shenzhen, CN;

Wei Yang, Shenzhen, CN;

Assignee:

Tencent Technology (Shenzhen) Company Limited, Shenzhen, CN;

Attorney:

ARENTFOX SCHIFF LLP

Primary Examiner:

Khai M Nguyen

Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06F 16/583 (2019.01); G06F 18/214 (2023.01); G06V 10/32 (2022.01); G06V 10/75 (2022.01); G06V 10/774 (2022.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01); G16H 70/20 (2018.01); A61B 5/055 (2006.01); A61B 6/00 (2006.01); A61B 8/08 (2006.01); G06F 17/11 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06F 16/5854 (2019.01); G06F 18/214 (2023.01); G06V 10/32 (2022.01); G06V 10/751 (2022.01); G06V 10/774 (2022.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01); G16H 70/20 (2018.01); A61B 5/055 (2013.01); A61B 6/5217 (2013.01); A61B 8/5223 (2013.01); G06F 17/11 (2013.01); G06V 2201/03 (2022.01);
Abstract

In a medical image recognition method, applied to a computer device, a to-be-recognized medical image set is obtained, where the to-be-recognized medical image set includes at least one to-be-recognized medical image. A to-be-recognized area corresponding to each to-be-recognized medical image in the to-be-recognized medical image set is extracted. The to-be-recognized area is a part of the to-be-recognized medical image. A recognition result of each to-be-recognized area through a medical image recognition model is determined. The medical image recognition model is obtained through training according to a medical image sample set. The medical image sample set includes at least one medical image sample, and each medical image sample carries corresponding annotation information. The annotation information is used for representing a type of the medical image sample, and the recognition result is used for representing the a of the to-be-recognized medical image.

Find Patent Forward Citations

Loading…