Structured sparsity through reweighting and application to diffusion MRI

Anna Auria, Alessandro Daducci, Jean-Philippe Thiran, Yves Wiaux

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We consider the problem of multiple correlated sparse signals reconstruction and propose a new implementation of struc- tured sparsity through a reweighting scheme. We present a particular application for diffusion Magnetic Resonance Imaging data and show how this procedure can be used for fi- bre orientation reconstruction in the white matter of the brain. In that framework, our structured sparsity prior can be used to exploit the fundamental coherence between fibre directions in neighbour voxels. Our method approaches the l0 minimi- sation through a reweighted l1-minimisation scheme. The weights are here defined in such a way to promote correlated sparsity between neighbour signals.
Original languageEnglish
Number of pages5
Publication statusPublished - 2015
Event23rd European Signal Processing Conference 2015 - Nice, France
Duration: 31 Aug 20154 Sept 2015


Conference23rd European Signal Processing Conference 2015
Abbreviated titleEUSIPCO 2015


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