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:
Oct. 28, 2025

Filed:

Jan. 29, 2021
Applicants:

Genentech, Inc., South San Francisco, CA (US);

Hoffmann-la Roche Inc., Little Falls, NJ (US);

Inventors:

Fillippo Arcadu, Basel, CH;

Benjamin Gutierrez-Becker, Basel, CH;

Andreas Thalhammer, Basel, CH;

Marco Prunotto, South San Francisco, CA (US);

Young Suk Oh, South San Francisco, CA (US);

Assignees:

HOFFMANN-LA ROCHE INC., Little Falls, NJ (US);

GENENTECH, INC., South San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); A61B 1/00 (2006.01); A61B 1/31 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); A61B 1/000096 (2022.02); A61B 1/31 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/10068 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30032 (2013.01); G06T 2207/30096 (2013.01); G06T 2207/30168 (2013.01);
Abstract

The application relates to devices and methods for analysing a colonoscopy video or a portion thereof, and for assessing the severity of ulcerative colitis in a subject by analysing a colonoscopy video obtained from the subject. Analysing a colonoscopy video comprises using a first deep neural network classifier to classify image data from the subject colonoscopy video or portion thereof into at least a first severity class (more severe endoscopic lesions) and a second severity class (less severe endoscopic lesions), wherein the first deep neural network has been trained at least in part in a weakly supervised manner using training image data from a plurality of training colonoscopy videos, the training image data comprising multiple sets of consecutive frames from the plurality of training colonoscopy videos, wherein frames in a set have the same severity class label. Devices and methods for providing a tool for analysing colonoscopy videos are also described.


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