Anna Auría

TL;DR: The encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent) is reported, however, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups.

TL;DR: The results demonstrate fundamental ambiguities inherent to tract reconstruction methods based on diffusion orientation information, with critical consequences for the approach of diffusion tractography in particular and human connectivity studies in general.

TL;DR: The approach reconciles voxelwise sparsity and spatial regularisation and defines a spatially structured FOD sparsity prior, where the structure originates from the spatial coherence of the fibre orientation between neighbour voxels.

TL;DR: In this paper, a linear convex approach for tensor recovery with built-in supersymmetry was proposed, and the inverse problem was regularized through a nuclear norm relaxation of a low-rank constraint.

TL;DR: A flexible framework is presented, based on convex optimisation, that enables fast and accurate reconstructions of the microstructure organisation, not limited to areas where the white matter is coherently oriented and the ability of the method to correctly estimate the microStructure features in crossing regions is shown.