title: Active contours driven by local and global intensity fitting energy with application to brain MR image segmentation.
abstract: In this paper, we propose an improved region-based active contour model in a variational level set formulation. We define an energy functional with a local intensity fitting term, which induces a local force to attract the contour and stops it at object boundaries, and an auxiliary global intensity fitting term, which drives the motion of the contour far away from object boundaries. Therefore, the combination of these two forces allows for flexible initialization of the contours. This energy is then incorporated into a level set formulation with a level set regularization term that is necessary for accurate computation in the corresponding level set method. The proposed model is first presented as a two-phase level set formulation and then extended to a multi-phase formulation. Experimental results show the advantages of our method in terms of accuracy and robustness. In particular, our method has been applied to brain MR image segmentation with desirable results.
authors.affiliation: School of Computer Science & Technology, Nanjing University of Science and Technology, Nanjing 210094, China. li.wang8401@gmail.com
authors.forename: Li
authors.initials: L
authors.lastname: Wang
authors.forename: Chunming
authors.initials: C
authors.lastname: Li
authors.forename: Quansen
authors.initials: Q
authors.lastname: Sun
authors.forename: Deshen
authors.initials: D
authors.lastname: Xia
authors.forename: Chiu-Yen
authors.initials: CY
authors.lastname: Kao
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data; D010363:Pattern Recognition, Automated / Q000379:methods