A Framework for Joint Diffusion Modelling and Orientation Estimation

Diffusion-Weighted MRI can reveal the microstructural organization of human brain white matter. In this work the diffusion model fitting is formulated as a global optimization problem assuming spatial coherence of the underlying diffusion parameters, which enables us to pool the variance from different voxels by their anatomical locations. The decision for single or multi-fiber voxels is directly integrated into the optimization process by using the Bayesian Information criterion. From a computational point of view the problem is quite hard, it is non-convex and combinatorial. At the heart of our approach lies a reversible jump Monte-Carlo Markov-Chain (RJMCMC) sampling strategy.

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