A spin glass based framework to untangle fiber crossing in MR diffusion based tracking

Abstract

We propose a general approach to the reconstruction of brain white matter geometry from diffusion-weighted data. This approach is based on an inverse problem framework. The optimal geometry corresponds to the lowest energy configuration of a spin glass. These spins represent pieces of fascicles that orient themselves according to diffusion data and interact in order to create lowcurvature fascicles. Simulated diffusion-weighted datasets corresponding to the crossing of two fascicle bundles are used to validate the method.