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- W825710008 abstract "We consider the problem of multiple correlated sparse signals reconstruction and propose a new implementation of structured 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 fibre 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 ℓ <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>0</sub> minimisation through a reweighted ℓ <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>1</sub> -minimisation scheme. The weights are here defined in such a way to promote correlated sparsity between neighbour signals." @default.
- W825710008 created "2016-06-24" @default.
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- W825710008 date "2015-08-01" @default.
- W825710008 modified "2023-10-02" @default.
- W825710008 title "Structured sparsity through reweighting and application to diffusion MRI" @default.
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- W825710008 doi "https://doi.org/10.1109/eusipco.2015.7362424" @default.
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