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Computational and Mathematical Methods in Medicine
Volume 2014, Article ID 890725, 10 pages
Research Article

Medical Image Segmentation Based on a Hybrid Region-Based Active Contour Model

1College of Information Science and Engineering, Ningbo University, Ningbo 315211, China
2College of Science & Technology, Ningbo University, Ningbo 315211, China

Received 20 February 2014; Revised 2 May 2014; Accepted 25 May 2014; Published 16 June 2014

Academic Editor: Peng Feng

Copyright © 2014 Tingting Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A novel hybrid region-based active contour model is presented to segment medical images with intensity inhomogeneity. The energy functional for the proposed model consists of three weighted terms: global term, local term, and regularization term. The total energy is incorporated into a level set formulation with a level set regularization term, from which a curve evolution equation is derived for energy minimization. Experiments on some synthetic and real images demonstrate that our model is more efficient compared with the localizing region-based active contours (LRBAC) method, proposed by Lankton, and more robust compared with the Chan-Vese (C-V) active contour model.