Learning-based aorta segmentation using an adaptive detach and merge algorithm
US9589211B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 8, 2015 |
| Grant date | Mar 7, 2017 |
| Priority date | — |
| Expiry date | May 8, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for segmenting a structure of interest in medical imaging data include generating a binary mask highlighting structures in medical imaging data, the highlighted structures comprising a connected component including a structure of interest. A probability map is computed by classifying voxels in the highlighted structures using a trained classifier. A plurality of detaching operations is performed on the highlighted structures to split the connected component into a plurality of detached connected components. An optimal detaching parameter is determined representing a number of the detaching operations. A detached connected component resulting from performing the number of detaching operations corresponding to the optimal detaching parameter is classified as the structure of interest based on the probability map and the trained classifier.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.