Elastic Registration of the Corpus Callosum

Geometric analysis of postmortem normal and autistic human subjects reveal distinctions in deformations in the corpus callosum (CC) that may be used for image analysis-based studies of autism. Preliminary studies showed that the CC of autistic patients is quite distinct from normal controls. We use an implicit vector representation of CC to carry out the registration process which measures the differences between different CC´s. This paper introduces a new method for the 2D shape registration problem by matching vector distance functions. A variational frame work is proposed for the global and local registration of CC´s. A gradient descent optimization is used which can efficiently handle both the rigid and the non-rigid operations together. The registration of real CC extracted from postmortem data sets demonstrates the potential of the proposed approach.