Cortex segmentation: a fast variational geometric approach.
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.
Goldenberg
Roman
R
Computer Science Department, Technion-Israel Institute of Technology, Technion City, Haifa 32000, Israel. romang@cs.technion.ac.il
Kimmel
Ron
R
Rivlin
Ehud
E
Rudzsky
Michael
M
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