Local Analysis of Cerebral Cortex

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. It is also important for many applications such as medical diagnosis, shape retrieval, and object alignment. 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 a 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, segmentation procedure using geometric curvature proprieties, that provide an efficient discrimination for local shape, is implemented on brain cortical surface. Experimental results demonstrate the effectiveness and the validity of our approach.