title: Cortex segmentation: a fast variational geometric approach.
abstract: An automatic cortical gray matter segmentation from a three-dimensional (3-D) brain images [magnetic resonance (MR) or computed tomography] is a well known problem in medical image processing. In this paper, we first formulate it as a geometric variational problem for propagation of two coupled bounding surfaces. An efficient numerical scheme is then used to implement the geodesic active surface model. Experimental results of cortex segmentation on real 3-D MR data are provided.
authors.affiliation: Computer Science Department, Technion-Israel Institute of Technology, Technion City, Haifa 32000, Israel. romang@cs.technion.ac.il
authors.forename: Roman
authors.initials: R
authors.lastname: Goldenberg
authors.forename: Ron
authors.initials: R
authors.lastname: Kimmel
authors.forename: Ehud
authors.initials: E
authors.lastname: Rivlin
authors.forename: Michael
authors.initials: M
authors.lastname: Rudzsky
mesh_terms: D000465:Algorithms; D019412:Anatomy, Cross-Sectional / Q000379:methods; D002540:Cerebral Cortex / Q000033:anatomy & histology* / Q000000981:diagnostic imaging; D003198:Computer Simulation; D016208:Databases, Factual; 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; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods