Atlas Warping for Brain Morphometry

In this work, we describe an automated approach to morphometry based on spatial normalizations of the data, and demonstrate its application to the analysis of gender diierences in the human corpus callosum. The purpose is to describe a population by a reduced and representative set of variables, from which a prior model can be constructed. Our approach is rooted in the assumption that individual anatomies can be considered as quantitative variations on a common underlying qualitative plan. We can therefore imagine that a given individual's anatomy is a warped version of some referential anatomy, also known as an atlas. The spatial warps which transform a labeled atlas into anatomic alignment with a population yield immediate knowledge about organ size and shape in the group. Furthermore, variation within the set of spatial warps is directly related to the anatomic variation among the subjects. Speciically, the shape statistics|mean and variance of the mappings|for the population can be calculated in a special basis, and an eigendecomposition of the variance performed to identify the most signiicant modes of shape variation. The results obtained with the corpus callosum study connrm the existence of substantial anatomical diierences between males and females, as reported in previous experimental work.