Bayesian Approach to the Brain Image Matching Problem

The application of image matching to the problem of localizing structural anatomy in images of the human brain forms the specic aim of our work. The interpretation of such images is a difficult task for human observers because of the many ways in which the identity of a given structure can be obscured. Our approach is based on the assumption that a common topology underlies the anatomy of normal individuals. To the degree that this assumption holds, the localization problem can be solved by determining the mapping from the anatomy of a given individual to some referential atlas of cerebral anatomy. Previous such approaches have in many cases relied on a physical interpretation of this mapping. In this paper, we examine a more general Bayesian formulation of the image matching problem and demonstrate the approach on two dimensional magnetic resonance images.