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. 15, 2020

Filed:

May. 18, 2018
Applicant:

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

Inventors:

Anant Madabhushi, Shaker Heights, OH (US);

Anna Gawlik, St. Charles, IL (US);

George Lee, Parlin, NJ (US);

Assignee:

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

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06T 7/00 (2017.01); G06T 7/60 (2017.01); G06T 7/11 (2017.01); G16H 30/40 (2018.01); G06K 9/62 (2006.01); G16H 50/30 (2018.01); G16H 50/50 (2018.01); G01N 15/14 (2006.01); G01N 33/574 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00147 (2013.01); G06K 9/00134 (2013.01); G06K 9/627 (2013.01); G06T 7/0014 (2013.01); G06T 7/11 (2017.01); G06T 7/60 (2013.01); G16H 30/40 (2018.01); G16H 50/30 (2018.01); G16H 50/50 (2018.01); G01N 15/1475 (2013.01); G01N 33/57434 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30081 (2013.01); G06T 2207/30096 (2013.01);
Abstract

Embodiments predict biochemical recurrence (BCR) or metastasis by accessing a set of images of a region of tissue demonstrating cancerous pathology, including a tumor region and a tumor adjacent benign (TAB) region, the set of images including a first stain type image, and a second stain type image; segmenting cellular nuclei represented in the first and second image; generating a combined feature set by extracting at least one feature from each of a tumor region and TAB region represented in the first image, and a tumor region and TAB region represented in the second image, providing the combined feature set to a machine learning classifier; receiving, from the classifier, a probability that the region of tissue will experience BCR or metastasis; and generating a classification of the region of tissue as likely to experience BCR or metastasis, or unlikely to experience BCR or metastasis.


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