Publications associées à Sparsity-Based Data Reconstruction Models for Biomedical Imaging

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Sparsistency of $\ell_1$-Regularized $M$-Estimators

Volkan Cevher, Jonathan Mark Scarlett, Yen-Huan Li

We consider the model selection consistency or sparsistency of a broad set of

\ell_1

-regularized

M

-estimators for linear and non-linear statistical models in a unified fashion. For this purpose, we propose the local structured smoothness condition (LSS ...

2015

Sparsity-Based Data Reconstruction Models for Biomedical Imaging

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Total Variation Regularization of Shape Signals

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Image Reconstruction in K-Space from MR Data Encoded with Ambiguous Gradient Fields

Isotropic Inverse-Problem Approach for Two-Dimensional Phase Unwrapping

Multitask diffusion LMS with sparsity-based regularization

Existence and Uniqueness of Maximal Regular Flows for Non-smooth Vector Fields

Sparse regularization for fiber ODF reconstruction: from the suboptimality of $\ell_2$ and $\ell_1$ priors to $\ell_0$

Digital Phase Reconstruction via Iterative Solutions of Transport-of-Intensity Equation

Digital Phase Reconstruction via Iterative Solutions of Transport-of-Intensity Equation

PURIFY: a new approach to radio-interferometric imaging

Multitask diffusion LMS with sparsity-based regularization

Total Variation Regularization of Shape Signals

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Image Reconstruction in K-Space from MR Data Encoded with Ambiguous Gradient Fields

Digital Phase Reconstruction via Iterative Solutions of Transport-of-Intensity Equation

Isotropic Inverse-Problem Approach for Two-Dimensional Phase Unwrapping

Existence and Uniqueness of Maximal Regular Flows for Non-smooth Vector Fields

PURIFY: a new approach to radio-interferometric imaging

Sparse regularization for fiber ODF reconstruction: from the suboptimality of $\ell_2$ and $\ell_1$ priors to $\ell_0$

Digital Phase Reconstruction via Iterative Solutions of Transport-of-Intensity Equation