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:
Feb. 13, 2024

Filed:

Dec. 09, 2020
Applicants:

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

The United States Government As Represented BY the Department of Veteran Affairs, Washington, DC (US);

Inventors:

Anant Madabhushi, Shaker Heights, OH (US);

Nathaniel Braman, Bethel Park, PA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06T 7/12 (2017.01); A61B 5/02 (2006.01); A61B 5/00 (2006.01); A61B 5/08 (2006.01);
U.S. Cl.
CPC ...
A61B 5/02007 (2013.01); A61B 5/004 (2013.01); A61B 5/0035 (2013.01); A61B 5/08 (2013.01); A61B 5/7267 (2013.01); A61B 5/7275 (2013.01); G06T 7/0012 (2013.01); G06T 7/12 (2017.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/20036 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30061 (2013.01); G06T 2207/30068 (2013.01); G06T 2207/30096 (2013.01); G06T 2207/30101 (2013.01);
Abstract

Embodiments discussed herein facilitate determination of a response to treatment and/or a prognosis for a tumor based at least in part on features of tumor-associated vasculature (TAV). One example embodiment is a method, comprising: accessing a medical imaging scan of a tumor, wherein the tumor is segmented on the medical imaging scan; segmenting tumor-associated vasculature (TAV) associated with the tumor based on the medical imaging scan; extracting one or more features from the TAV; providing the one or more features extracted from the TAV to a trained machine learning model; and receiving, from the machine learning model, one of a predicted response to a treatment for the tumor or a prognosis for the tumor.


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