Deep learning for arterial analysis and assessment
US10964017B2 · kind B2 · utility
10Cited by
8References
12Claims
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Key dates
| Filing date | Nov 15, 2018 |
| Grant date | Mar 30, 2021 |
| Priority date | — |
| Expiry date | May 11, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30104
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
The present disclosure relates to training one or more neural networks for vascular vessel assessment using synthetic image data for which ground-truth data is known. In certain implementations, the synthetic image data may be based in part, or derived from, clinical image data for which ground-truth data is not known or available. Neural networks trained in this manner may be used to perform one or more of vessel segmentation, decalcification, Hounsfield unit scoring, and/or estimation of a hemodynamic parameter.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.