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:
Jan. 28, 2025

Filed:

Oct. 20, 2020
Applicants:

University of Cincinnati, Cincinnati, OH (US);

Children's Hospital Medical Center, Cincinnati, OH (US);

Inventors:

Jinghua Wang, Mason, OH (US);

Lili He, Mason, OH (US);

Assignees:

University of Cincinnati, Cincinnati, OH (US);

Children's Hospital Medical Center, Cincinnati, OH (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/00 (2006.01); G06T 7/00 (2017.01); G06T 7/45 (2017.01); G06T 7/62 (2017.01); G06V 10/44 (2022.01); G06V 10/82 (2022.01); G06V 20/69 (2022.01);
U.S. Cl.
CPC ...
A61B 5/4848 (2013.01); G06T 7/0016 (2013.01); G06T 7/45 (2017.01); G06T 7/62 (2017.01); G06V 10/454 (2022.01); G06V 10/82 (2022.01); G06V 20/695 (2022.01); G06T 2207/10064 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10104 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30016 (2013.01); G06T 2207/30096 (2013.01); G06T 2207/30242 (2013.01);
Abstract

A method or system for assessing a patient response to a cancer treatment is provided. The method or system includes acquiring at least one base-line radiological image related to a patient immediately before a treatment, acquiring at least one follow-up radiological image during or after the treatment at a predetermined time interval, estimating a first number of specific tumor cells in a region of interest of the patient based on image features of the base-line radiological image using an algorithm or a model, estimating a second number of specific tumor cells in the region of interest of the patient based on image features of the follow-up radiological image using the algorithm or the model, obtaining a difference between the first number of specific tumor cells and the second number of specific tumor cells, and classifying a treatment response to a cancer based on the difference.


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