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:
Apr. 23, 2024

Filed:

May. 13, 2021
Applicant:

Merative Us L.p., Ann Arbor, MI (US);

Inventors:

Shafiqul Abedin, San Jose, CA (US);

Hongzhi Wang, Santa Bruno, CA (US);

Ehsan Dehghan Marvast, Palo Alto, CA (US);

David James Beymer, San Jose, CA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06F 18/2433 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G06T 7/11 (2017.01); G06V 10/34 (2022.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06F 18/2433 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06T 7/11 (2017.01); G06V 10/34 (2022.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01);
Abstract

A candidate generator generates a set of candidate three-dimensional image patches from an input volume. A candidate classifier classifies the set of candidate three-dimensional image patches as containing or not containing disease. Classifying the set of candidate three-dimensional image patches comprises generating an attention mask for each given candidate three-dimensional image patch within the set of candidate three-dimensional image patches to form a set of attention masks, applying the set of attention masks to the set of candidate three-dimensional image patches to form a set of masked image patches, and classifying the set of masked image patches as containing or not containing the disease. The candidate classifier applies soft attention and hard attention to the three-dimensional image patches such that distinctive image regions are highlighted proportionally to their contribution to classification while completely removing image regions that may cause confusion.


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