Jakub Piatkowski1, Amos J. Storkey2, Mark E. Bastin3
1Neuroinformatics Doctoral Training Centre, University of Edinburgh, Edinburgh, United Kingdom; 2Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom; 3Medical Physics, University of Edinburgh, Edinburgh, Midlothian, United Kingdom
We use a fully physical two-compartment model, comprising isotropic and anisotropic terms, to describe diffusion MRI data. The posterior distributions over the parameters of this model are estimated using sampling techniques. This yields maps of white matter (WM) volume, which reveal a level of structure missing in FA maps. Additionally, we get tensor parameters for the anisotropic compartment (i.e. WM), which provide a measure of fibre-specific anisotropy that doesn't suffer from partial volume effects.