Method and system for vascular disease detection using recurrent neural networks
US9767557B1 · kind B1 · utility
96Cited by
6References
27Claims
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Key dates
| Filing date | Feb 10, 2017 |
| Grant date | Sep 19, 2017 |
| Priority date | — |
| Expiry date | Feb 10, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30172
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and apparatus for vascular disease detection and characterization using a recurrent neural network (RNN) is disclosed. A plurality of 2D cross-section image patches are extracted from a 3D computed tomography angiography (CTA) image, each extracted at a respective sampling point along a vessel centerline of a vessel of interest in the 3D CTA image. Vascular abnormalities in the vessel of interest are detected and characterized by classifying each of the sampling points along the vessel centerline based on the plurality of 2D cross-section image patches using a trained RNN.
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