Medical image segmentation using active contour driven by local energy and minimal variance

Authors:
Haijun Wang;Ming Liu;Shouxi Zhu
Affiliations:
Flying College, Flying College, Bin Zhou, China;Flying College, Flying College, Bin Zhou, China;Flying College, Flying College, Bin Zhou, China
Venue:
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 1
Year:
2010

Citing 6
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Abstract

In this paper, we simplify the model of local binary model and propose an improved region-based active contour model for medical image segmentation. Our model combines the advantages of the simplification of local binary fitting model by taking the local intensity information and the speed function using the minimal variance term, which enable the model to cope with intensity inhomogeneity. We define an energy functional with a local intensity fitting term and the minimal variance term. In the associated curve evolution, the motion of the contour is driven by a local intensity fitting force and the minimal variance force that make the contour evolve to the edge wherever it is. The proposed model has been applied to medical image segmentation with promising results.