Medical Image Segmentation Based on a Hybrid Region-Based Active Contour Model. (16th June 2014)

• Record Type: Journal Article
• Authors: Liu, Tingting; Xu, Haiyong; Jin, Wei; Liu, Zhen; Zhao, Yiming; Tian, Wenzhe
• Other Names: Feng Peng Academic Editor.
• Is Part Of: Computational and mathematical methods in medicine. Volume 2014(2014)
• Publication Date: 2014-06-16
• Subjects: Medicine -- Computer simulation -- Periodicals; Medicine -- Mathematical models -- Periodicals; 610.11
• DOI: 10.1155/2014/890725
• Languages: English
• ISSNs: 1748-670X

Abstract

Abstract : 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.