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:
Jun. 17, 2025

Filed:

Oct. 14, 2020
Applicant:

University of Pittsburgh—of the Commonwealth System of Higher Education, Pittsburgh, PA (US);

Inventors:

Timothy K. Chung, Pittsburgh, PA (US);

David A. Vorp, Pittsburgh, PA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/00 (2006.01); G06T 7/00 (2017.01); G06T 7/13 (2017.01); G06T 7/60 (2017.01); G06T 17/00 (2006.01); G06V 10/26 (2022.01); G06V 10/75 (2022.01); G06V 20/64 (2022.01);
U.S. Cl.
CPC ...
A61B 5/7267 (2013.01); G06T 7/0012 (2013.01); G06T 7/13 (2017.01); G06T 7/60 (2013.01); G06T 17/00 (2013.01); G06V 10/26 (2022.01); G06V 10/754 (2022.01); G06V 20/653 (2022.01); G06T 2207/20084 (2013.01); G06T 2207/30048 (2013.01); G06T 2207/30101 (2013.01);
Abstract

Disclosed herein are related to a system, a method, and a non-transitory computer readable medium for simulating, predicting, or estimating, based on machine learning neural networks, wall stress of a body part. In one approach, a first neural network automatically detects features in multiple images of a body part. For example, the first neural network may detect, for each image, a lumen and a wall of an aorta. According to the detected features, a second neural network may simulate, estimate, or predict wall stress of the body part in response to pressure applied to the body part. For example, a model generator can generate a three-dimensional model of the body part according to the detected features in the multiple images, and the second neural network can simulate, estimate, or predict wall stress of the body part according to the three-dimensional model.


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