title: Local analysis of human cortex in MRI brain volume.
abstract: This paper describes a method for subcortical identification and labeling of 3D medical MRI images. Indeed, the ability to identify similarities between the most characteristic subcortical structures such as sulci and gyri is helpful for human brain mapping studies in general and medical diagnosis in particular. However, these structures vary greatly from one individual to another because they have different geometric properties. For this purpose, we have developed an efficient tool that allows a user to start with brain imaging, to segment the border gray/white matter, to simplify the obtained cortex surface, and to describe this shape locally in order to identify homogeneous features. In this paper, a segmentation procedure using geometric curvature properties that provide an efficient discrimination for local shape is implemented on the brain cortical surface. Experimental results demonstrate the effectiveness and the validity of our approach.
authors.affiliation: Université de Tunis El Manar, École Nationale d'Ingénieurs de Tunis, BP 37 Belvedere Tunis, 1002 Tunis, Tunisia ; College of Computers and Information Technology, Taif University, P.O. Box 888, Taif 21974, Saudi Arabia.
authors.forename: Sami
authors.identifier: 0000-0002-6638-7039
authors.initials: S
authors.lastname: Bourouis
mesh_terms: D000465:Algorithms; D002540:Cerebral Cortex / Q000502:physiology*; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*