Sparse recovery in magnetic resonance imaging with a Markov random field prior

Augmented Lagrangian based reconstruction of non-uniformly sub-Nyquist sampled MRI data

On structured sparsity and selected applications in tomographic imaging

This work explores the potentials of structure encoding in sparse tomographic reconstructions. We are encoding spatial structure with Markov Random Field (MRF) models and employ it within Magnetic Resonance Imaging (MRI) and Quantitative Microwave …