Homogeneity- and density distance-driven active contours for medical image segmentation

Authors:
Phan Tran Ho Truc;Tae-Seong Kim;Sungyoung Lee;Young-Koo Lee
Affiliations:
Department of Computer Engineering, Kyung Hee University, Repuplic of Korea;Department of Biomedical Engineering, Kyung Hee University, Republic of Korea;Department of Computer Engineering, Kyung Hee University, Repuplic of Korea;Department of Computer Engineering, Kyung Hee University, Repuplic of Korea
Venue:
Computers in Biology and Medicine
Year:
2011

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Abstract

In this paper, we present a novel active contour (AC) model for medical image segmentation that is based on a convex combination of two energy functionals to both minimize the inhomogeneity within an object and maximize the distance between the object and the background. This combination is necessary because objects in medical images, e.g., bones, are usually highly inhomogeneous while distinct organs should generate distinct image configurations. Compared with the conventional Chan-Vese AC, the proposed model yields similar performance in a set of CT images but performs better in an MRI data set, which is generally in lower contrast.