Automatic method and system for vessel refine segmentation in biomedical images using tree structure based deep learning model
US10430949B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 23, 2019 |
| Grant date | Oct 1, 2019 |
| Priority date | — |
| Expiry date | Apr 23, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30101
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments of the disclosure provide systems and methods for segmenting a biomedical image including at least one tree structure object. The system includes a communication interface configured to receive the biomedical image and a learning model. The biomedical image is acquired by an image acquisition device. The system further includes at least one processor configured to extract a plurality of image patches from the biomedical image and apply the learning model to the plurality of image patches to segment the biomedical image. The learning model includes a convolutional network configured to process the plurality of image patches to construct respective feature maps and a tree structure network configured to process the feature maps collectively to obtain a segmentation mask for the tree structure object. The tree structure network models a spatial constraint of the plurality of image patches.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.