Medical image segmentation using an integrated edge guidance module and object segmentation network
US10482603B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 25, 2019 |
| Grant date | Nov 19, 2019 |
| Priority date | — |
| Expiry date | Jun 25, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30061
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
This disclosure relates to improved techniques for performing image segmentation functions using neural network architectures. The neural network architecture integrates an edge guidance module and object segmentation network into a single framework for detecting target objects and performing segmentation functions. The neural network architecture can be trained to generate edge-attention representations that preserve the edge information included in images. The neural network architecture can be trained to generate multi-scale feature information that preserves and enhances object-level feature information included in images. The edge-attention representations and multi-scale feature information can be fused to generate segmentation results that identify target object boundaries with increased accuracy.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.