Inferring brain variability from diffeomorphic deformations of currents: an integrative approach.

ABSTRACT: In the context of computational anatomy, one aims at understanding and modelling the anatomy of the brain and its variations across a population. This geometrical variability is often measured from precisely defined anatomical landmarks such as sulcal lines or meshes of brain structures. This requires (1) to compare geometrical objects without introducing too many non realistic priors and (2) to retrieve the variability of the whole brain from the variability of the landmarks. We propose, in this paper, to infer a statistical brain model from the consistent integration of variability of sulcal lines. The similarity between two sets of lines is measured by a distance on currents that does not assume any type of point correspondences and it is not sensitive to the sampling of lines. This sha

SUBMITTER: Durrleman S 

PROVIDER: S-EPMC2572735 | biostudies-literature | 2008 Oct

REPOSITORIES: biostudies-literature