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:
Nov. 09, 2021

Filed:

Oct. 30, 2019
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Roie Melamed, Haifa, IL;

Lior Ness, Ra'anana, IL;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); A61B 6/00 (2006.01); A61B 5/00 (2006.01); G06K 9/32 (2006.01); G06K 9/34 (2006.01); G06N 20/00 (2019.01); G06K 9/46 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); A61B 5/7267 (2013.01); A61B 6/502 (2013.01); A61B 6/5217 (2013.01); G06K 9/3233 (2013.01); G06K 9/34 (2013.01); G06K 9/4652 (2013.01); G06N 20/00 (2019.01); G06T 2207/20081 (2013.01); G06T 2207/30061 (2013.01); G06T 2207/30068 (2013.01); G06T 2207/30096 (2013.01);
Abstract

There is provided a computer implemented method for detection of likelihood of malignancy in an anatomical image of a patient for treatment planning, comprising: receiving an anatomical image, feeding the anatomical image into a global component of a model trained to output a global classification label, feeding the anatomical image into a local component of the model trained to output a localized boundary, feeding the anatomical image patch-wise into a patch component of the model trained to output a patch level classification label, extracting a respective set of regions of interest (ROIs) from each one of the components, each ROI indicative of a region of the anatomical image likely to include an indication of malignancy, aggregating the ROIs from each one of the components into an aggregated set of ROIs, and feeding the aggregated set of ROIs into an output component that outputs an indication of likelihood of malignancy.


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