Publications by Anna Auria Rasclosa

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Mapping the local microstructure properties of the tissue in the brain is crucial to understand any pathological condition from a biological perspective. In recent years, microstructure-imaging techniques aimed at extracting such precious information by us ...

We propose a novel formulation to solve the problem of intra-voxel reconstruction of the fibre orientation distribution function (FOD) in each voxel of the white matter of the brain from diffusion MRI data. The majority of the state-of-the-art methods in t ...

Image recovery in optical interferometry is an ill-posed nonlinear inverse problem arising from incomplete power spectrum and bispectrum measurements. We reformulate this nonlin- ear problem as a linear problem for the supersymmetric rank-1 order-3 tensor ...

Many natural images have low intrinsic dimension (a.k.a. sparse), meaning that they can be represented with very few coefficients when expressed in an adequate domain. The recent theory of Compressed Sensing exploits this property offering a powerful frame ...

Axon Diameter Distributions (ADDs) change during brain development and are altered in several brain pathologies. Mapping ADDs non-invasively using dMRI could provide a useful biomarker, but existing methods are either parametric, orientation dependent, sur ...

Microstructure imaging with diffusion MRI (dMRI) is usually based on fitting models to the data using voxelwise nonlinear procedures that (i) are time consuming and (ii) need long acquisitions. Recently, we introduced the AMICO framework to accelerate the ...

State-of-the-art microstructure imaging methods usually fit biophysical models to the diffusion MRI data on a voxel-by-voxel basis using non-linear procedures that require both long acquisitions and processing time. We recently introduced AMICO, a framewor ...

Diffusion MRI is a well established imaging modality providing a powerful way to non-invasively probe the structure of the white matter. Despite the potential of the technique, the intrinsic long scan times of these sequences have hampered their use in cli ...

Image recovery in optical interferometry is an ill-posed nonlinear inverse problem arising from incomplete power spectrum and bispectrum measurements. We review our previous work, which reformulates this nonlinear problem in the framework of tensor recover ...

Image recovery in optical interferometry is an ill-posed nonlinear inverse problem arising from incomplete power spectrum and bi-spectrum measurements. We formulate a linear version of the problem for the order-3 tensor formed by the tensor product of the ...

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 ho ...

Anna Auria Rasclosa

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Accelerated Microstructure Imaging via Convex Optimization (AMICO) in crossing fibers

Structured sparsity for spatially coherent fibre orientation estimation in diffusion MRI

Tensor optimisation for optical-interferometric imaging

Sparse inverse problems for Fourier imaging : applications to Optical Interferometry and Diffusion Magnetic Resonance Imaging

Orientation invariant and non-parametric Axon Diameter Distribution mapping using PGSE and regularized discrete linear modeling

Reducing acquisition time for microstructure imaging with spatially-regularized global optimization

Reducing acquisition time for axon diameter mapping using global optimization in the spatial-angular-microstructure space

l0-deconvolution for compressive diffusion MRI

Sparsity in tensor optimization for optical-interferometric imaging

A convex optimization approach for image recovery from nonlinear measurements in optical interferometry

Structured sparsity through reweighting and application to diffusion MRI