Method and system for vascular disease detection using recurrent neural networks
US9881372B2 · kind B2 · utility
63Cited by
8References
26Claims
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Key dates
| Filing date | Aug 18, 2017 |
| Grant date | Jan 30, 2018 |
| Priority date | — |
| Expiry date | Aug 18, 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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