Machine learning based triple region segmentation framework using level set on PACS
US8073253B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 13, 2007 |
| Grant date | Dec 6, 2011 |
| Priority date | — |
| Expiry date | Oct 5, 2030 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30016
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Certain embodiments of the present invention provide methods and systems for triple region image segmentation. Certain embodiments provide a method for triple region image segmentation on a picture archiving and communication system. The method includes forming an initial contour for an image including three regions using principal component analysis and a support vector machine. The method also includes segmenting the image into three regions using a single level set function based on the initial contour. Certain embodiments provide an image processing system facilitating triple region segmentation of an image. The system includes a pattern classifier including a support vector machine, the pattern classifier forming an initial contour for an image including three regions using principal component analysis and the support vector machine. The system also includes a triple region segmenter segmenting the image into three regions using a single level set function based on the initial contour.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.