Stress prediction based on neural network
US12329546B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 14, 2020 |
| Grant date | Jun 17, 2025 |
| Priority date | — |
| Expiry date | Nov 29, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.