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

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Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

Michaël Unser, Julien René Pierre Fageot, Harshit Gupta

We present a theoretical analysis and comparison of the effect of

ℓ _{ 1 }

versus

ℓ _{ 2 }

regularization for the resolution of ill-posed linear inverse and/or compressed sensing problems. Our formulation covers the most general setting where the s ...

IEEE2016

Sparsity-Based Data Reconstruction Models for Biomedical Imaging

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Optical Tomographic Image Reconstruction Based on Beam Propagation and Sparse Regularization

Mumford-Shah and Potts Regularization for Manifold-Valued Data

Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

Morphological component analysis for sparse regularization in plane wave imaging

Principled Parallel Mean-Field Inference for Discrete Random Fields

Slice-by-Slice versus Fully 3D Reconstruction for Parallel-Beam x-Ray Microtomography

A Forward Regridding Method with Minimal Oversampling for Accurate and Efficient Iterative Tomographic Algorithms

Improved Variational Denoising of Flow Fields with Application to Phase-Contrast MRI Data

An Algorithmic Framework for Mumford-Shah Regularization of Inverse Problems in Imaging

A Modulated Closed Form solution for Quantitative Susceptibility Mapping - A thorough evaluation and comparison to iterative methods based on edge prior knowledge

An Algorithmic Framework for Mumford-Shah Regularization of Inverse Problems in Imaging

A Forward Regridding Method with Minimal Oversampling for Accurate and Efficient Iterative Tomographic Algorithms

Slice-by-Slice versus Fully 3D Reconstruction for Parallel-Beam x-Ray Microtomography

Principled Parallel Mean-Field Inference for Discrete Random Fields

Morphological component analysis for sparse regularization in plane wave imaging

Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

Mumford-Shah and Potts Regularization for Manifold-Valued Data

Optical Tomographic Image Reconstruction Based on Beam Propagation and Sparse Regularization

A Modulated Closed Form solution for Quantitative Susceptibility Mapping - A thorough evaluation and comparison to iterative methods based on edge prior knowledge

Improved Variational Denoising of Flow Fields with Application to Phase-Contrast MRI Data