Medical image segmentation based on novel local order energy

Authors:
Ling Feng Wang;Zeyun Yu;ChunHong Pan
Affiliations:
NLPR, Institute of Automation, Chinese Academy of Sciences;Department of Computer Science University of Wisconsin-Milwaukee;NLPR, Institute of Automation, Chinese Academy of Sciences
Venue:
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
Year:
2010

Citing 11
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Abstract

Image segmentation plays an important role in many medical imaging systems, yet in complex circumstances it is still a challenging problem. Among many difficulties, problem caused by the image intensity inhomogeneity is the key aspect. In this work, we develop a novel localhomogeneous region-based level set segmentation method to tackle this problem. First, we propose a novel local order energy, which interprets the local intensity constraint. And then, we integrate this energy into the objective energy function. After that, we minimize the energy function via a level set evolution process. Extensive experiments are performed to evaluate the proposed approach, showing significant improvements in both accuracy and efficiency, as compared to the state-of-the-art.