Cortex segmentation: a fast variational geometric approach

Author

Goldenberg, Roman ; Kimmel, Ron ; Rivlin, Ehud ; Rudzsky, Michael

Author_Institution

Comput. Sci. Dept., Technion Israel Inst. of Technol., Haifa, Israel

Volume

21

Issue

12

fYear

2002

Firstpage

1544

Lastpage

1551

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.

Keywords

biomedical MRI; brain models; computerised tomography; image segmentation; medical image processing; 3-D MR data; cerebral spinal fluid; cortical surface segmentation; deformable coupled surfaces; efficient numerical scheme; geodesic active contours; level-sets; medical diagnostic imaging; three-dimensional brain images; two coupled bounding surfaces; Active contours; Brain modeling; Cities and towns; Computer science; Deformable models; Image segmentation; Magnetic resonance; Rough surfaces; Surface reconstruction; Surface roughness; Algorithms; Anatomy, Cross-Sectional; Cerebral Cortex; Computer Simulation; Databases, Factual; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Tomography, X-Ray Computed;

fLanguage

English

Journal_Title

Medical Imaging, IEEE Transactions on

Publisher

ieee

ISSN

0278-0062

Type

jour

DOI

10.1109/TMI.2002.806594

Filename

1176642