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. 19, 2017

Filed:

Dec. 10, 2015
Applicant:

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

Inventors:

Anant Madabhushi, Beachwood, OH (US);

Mirabela Rusu, Cleveland, OH (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); A61B 6/03 (2006.01); G06T 11/00 (2006.01); G06K 9/62 (2006.01); G06K 9/46 (2006.01); G06K 9/66 (2006.01); C07K 16/28 (2006.01); C07K 16/46 (2006.01); G06T 7/11 (2017.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); A61B 6/032 (2013.01); C07K 16/2803 (2013.01); C07K 16/468 (2013.01); G06K 9/4604 (2013.01); G06K 9/6267 (2013.01); G06K 9/66 (2013.01); G06T 7/11 (2017.01); G06T 11/003 (2013.01); C07K 2317/31 (2013.01); C07K 2317/41 (2013.01); C07K 2317/524 (2013.01); C07K 2317/526 (2013.01); C07K 2317/622 (2013.01); C07K 2317/64 (2013.01); C07K 2317/71 (2013.01); C07K 2317/92 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/30024 (2013.01); G06T 2207/30061 (2013.01); G06T 2207/30096 (2013.01);
Abstract

Methods and apparatus associated with distinguishing invasive adenocarcinoma (IA) from in situ adenocarcinoma (AIS) are described. One example apparatus includes a set of logics, and a data store that stores three dimensional (3D) radiological images of tissue demonstrating IA or AIS. The set of logics includes a classification logic that generates an invasiveness classification for a diagnostic 3D radiological image, a training logic that trains the classification logic to identify a texture feature associated with IA, an image acquisition logic that acquires a diagnostic 3D radiological image of a region of tissue demonstrating cancerous pathology and that provides the diagnostic 3D radiological image to the classification logic, and a prediction logic that generates an invasiveness score based on the diagnostic 3D radiological image and the invasiveness classification. The training logic trains the classification logic using a set of 3D histological reconstructions combined with the set of 3D radiological images.


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