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:
Jul. 15, 2025

Filed:

Aug. 30, 2022
Applicant:

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

Inventors:

Gregory Zelinsky Ferl, South San Francisco, CA (US);

Richard Alan Duray Carano, South San Francisco, CA (US);

Kai Henrik Barck, South San Francisco, CA (US);

Jasmine Patil, South San Francisco, CA (US);

Assignee:

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

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06T 7/11 (2017.01); G06V 10/774 (2022.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06T 7/11 (2017.01); G06V 10/774 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/30096 (2013.01); G06V 2201/031 (2022.01);
Abstract

Methods and systems disclosed herein relate generally to processing images to estimate whether at least part of a tumor is represented in the images. A computer-implemented method includes accessing an image of at least part of a biological structure of a particular subject, processing the image using a segmentation algorithm to extract a plurality of image objects depicted in the image, determining one or more structural characteristics associated with an image object of the plurality of image objects, processing the one or more structural characteristics using a trained machine-learning model to generate estimation data corresponding to an estimation of whether the image object corresponds to a lesion or tumor associated with the biological structure, and outputting the estimation data for the particular subject.


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