A robust region based level set framework for medical image segmentation

Authors:
Yong Yang
Affiliations:
School of Information Management, Jiangxi University of Finance and Economics, Nanchang, P.R. China
Venue:
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Year:
2006

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Abstract

In this paper, we present new developments in the formulation of a new class of level set method for medical image segmentation. In this work, a new speed function of level set framework is proposed. The region statistical information, instead of the conventional image gradient information, is fused into the level set fundamental model to improve the robustness of the segmentation for medical images. The new method has some advantages over classical level set methods especially in the situations where edges are weak and fuzzy. A number of experiments on MR, US and CT images were performed to evaluate the new method. Experimental results are given to illustrate the effectiveness and robustness of the method.