title: A generalized level set formulation of the Mumford-Shah functional for brain MR image segmentation.
abstract: Brain MR image segmentation is an important research topic in medical image analysis area. In this paper, we propose an active contour model for brain MR image segmentation, based on a generalized level set formulation of the Mumford-Shah functional. The model embeds explicitly gradient information into the Mumford-Shah functional, and incorporates in a generic framework both regional and gradient information into segmentation process simultaneously. The proposed method has been evaluated on real brain MR images and the obtained results have shown the desirable segmentation performance.
authors.affiliation: Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University (SJTU), Shanghai 200030, PR China. lishuicheng@sjtu.edu.cn
authors.forename: Lishui
authors.initials: L
authors.lastname: Cheng
authors.forename: Jie
authors.initials: J
authors.lastname: Yang
authors.forename: Xian
authors.initials: X
authors.lastname: Fan
authors.forename: Yuemin
authors.initials: Y
authors.lastname: Zhu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*