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:
Sep. 08, 2020

Filed:

Dec. 12, 2018
Applicant:

Case Western Reserve University, Cleveland, OH (US);

Inventors:

Anant Madabhushi, Shaker Heights, OH (US);

Patrick Leo, Honoeye Falls, NY (US);

Andrew Janowczyk, East Meadow, NY (US);

Sanjay Gupta, Mayfield Heights, OH (US);

Assignee:

Case Western Reserve University, Cleveland, OH (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06K 9/62 (2006.01); G06K 9/00 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06K 9/0014 (2013.01); G06K 9/6202 (2013.01); G06K 9/6223 (2013.01); G06K 9/6277 (2013.01); G06T 2207/20036 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30024 (2013.01);
Abstract

Embodiments include controlling a processor to perform operations for predicting biochemical recurrence (BCR) in prostate cancer (PCa), including accessing a first digitized pathology slide having a first stain channel of a region of tissue demonstrating PCa; accessing a second digitized pathology slide having a second, different stain channel of the region of tissue; extracting morphology features from the first stain channel; extracting stain intensity features from the second stain channel, where a stain intensity feature quantifies an amount of a molecular biomarker present in a cellular nucleus; controlling a first machine learning classifier to generate a first probability of BCR based on the morphology features; controlling a second machine learning classifier to generate a second, different probability of BCR based on the stain intensity features; computing an aggregate probability of BCR based on the first probability and the second probability; and displaying the aggregate probability.


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