Hierarchical brain mapping via a generalized Dirichlet solution for mapping brain manifolds

Abstract

In this paper we present a coarse-to-fine approach for the transformation of digital anatomical textbooks from the ideal to the individual that unifies the work on landmark deformations and v olume based transformation. The Hierarchical approach is linked to the Biological problem itself, coming out of the various kinds of information which is provided by the anatomists. This information is in the form of points, lines, surfaces and subvolumes corresponding to 0,1,2 and 3 dimensional submanifolds respectively. The algorithm is driven by these submanifolds. We follow the approach that the highest dimensional transformation is a result from the solution of a sequence of lower dimensional problems driven by successive refinements or partitions of the images in to various Biologically meaningful substructures.