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:
May. 03, 2022

Filed:

Sep. 22, 2020
Applicant:

Applied Materials, Inc., Santa Clara, CA (US);

Inventors:

Sumit Kumar Jha, Jharkhand, IN;

Aditya Sista, Bangalore, IN;

Ganesh Kumar Mohanur Raghunathan, Bangalore, IN;

Ubhay Kumar, Bihar, IN;

Kedar Sapre, San Jose, CA (US);

Assignee:

Applied Materials, Inc., Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06T 7/00 (2017.01); G06T 7/11 (2017.01); G06K 9/62 (2022.01); G06V 10/25 (2022.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06K 9/6215 (2013.01); G06K 9/6282 (2013.01); G06T 7/11 (2017.01); G06V 10/25 (2022.01); G06T 2207/10056 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30024 (2013.01);
Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model to segment magnified images of tissue samples. The method includes obtaining a magnified image of a tissue sample; processing an input comprising: the image, features derived from the image, or both, in accordance with current values of model parameters of a machine learning model to generate an automatic segmentation of the image into a plurality of tissue classes; providing, to a user through a user interface, an indication of: (i) the image, and (ii) the automatic segmentation of the image; determining an edited segmentation of the image, comprising applying modifications specified by the user to the automatic segmentation of the image; and determining updated values of the model parameters of the machine learning model based the edited segmentation of the image.


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