A framework based on spin glass models for the inference of anatomical connectivity from diffusion-weighted MR data - a technical review.

Abstract

A family of methods aiming at the reconstruction of a putative fascicle map from any diffusion-weighted dataset is proposed. This fascicle map is defined as a trade-off between local information on voxel microstructure provided by diffusion data and a priori information on the low curvature of plausible fascicles. The optimal fascicle map is the minimum energy configuration of a simulated spin glass in which each spin represents a fascicle piece. This spin glass is embedded into a simulated magnetic external field that tends to align the spins along the more probable fiber orientations according to diffusion models. A model of spin interactions related to the curvature of the underlying fascicles introduces a low bending potential constraint. Hence, the optimal configuration is a trade-off between these two kind of forces acting on the spins. Experimental results are presented for the simplest spin glass model made up of compass needles located in the center of each voxel of a tensor based acquisition.