Quantitative study of brain anatomy

Abstract

The authors introduce a system that automatically segments and classifies features in brain MRIs. It takes 22 minutes to segment 144 structures in a 256/spl times/256/spl times/124 voxel image on an SGI computer with three 194 MHz RIOK processors. The accuracy is comparable to manual segmentation, which can take an expert at least 8 months. The process starts with an atlas, a hand segmented and classified MRI of a normal brain. Given a subject's data, the atlas is warped in 3-D using a hierarchical deformable matching algorithm until it closely matches the subject, i.e. the atlas is customized for the subject. The customized atlas contains the segmentation and classification of the subject's anatomical structures. Qualitative and quantitative evaluations of the system's performance show promise for applications in the quantitative study of brain anatomy. The authors have obtained initial results for finding the normal range of variation in the size and symmetry properties of anatomical structures, and for detecting pathologies.