Shape Analysis of Corpus Callosum in Phenylketonuria Using a ew 3D Correspondence Algorithm

Statistical shape analysis of brain structures has gained increasing interest from neuroimaging community because it can precisely locate shape differences between healthy and pathological structures. The most difficult and crucial problem is establishing shape correspondence among individual 3D shapes. This paper proposes a new algorithm for 3D shape correspondence. A set of landmarks are sampled on a template shape, and initial correspondence is established between the template and the target shape based on the similarity of locations and normal directions. The landmarks on the target are then refined by iterative thin plate spline. The algorithm is simple and fast, and no spherical mapping is needed. We apply our method to the statistical shape analysis of the corpus callosum (CC) in phenylketonuria (PKU), and significant local shape differences between the patients and the controls are found in the most anterior and posterior aspects of the corpus callosum.