Medical image segmentation based on the minimum variation snake model.
- Author:
Changxiong ZHOU
1
;
Shenglin YU
Author Information
1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautic, Nanjing 210016, China.
- Publication Type:Journal Article
- MeSH:
Diagnostic Imaging;
Humans;
Image Processing, Computer-Assisted;
methods;
Models, Theoretical
- From:
Journal of Biomedical Engineering
2007;24(1):32-35
- CountryChina
- Language:Chinese
-
Abstract:
It is difficult for traditional parametric active contour (Snake) model to deal with automatic segmentation of weak edge medical image. After analyzing snake and geometric active contour model, a minimum variation snake model was proposed and successfully applied to weak edge medical image segmentation. This proposed model replaces constant force in the balloon snake model by variable force incorporating foreground and background two regions information. It drives curve to evolve with the criterion of the minimum variation of foreground and background two regions. Experiments and results have proved that the proposed model is robust to initial contours placements and can segment weak edge medical image automatically. Besides, the testing for segmentation on the noise medical image filtered by curvature flow filter, which preserves edge features, shows a significant effect.
