1 citations · 1 across the 4 of their papers we have counts for
7 papers
Hybrid learning of Non-Cartesian k-space trajectory and MR image reconstruction networks
Chaithya G R, Zaccharie Ramzi, Philippe Ciuciu
Compressed sensing (CS) in Magnetic resonance Imaging (MRI) essentially involves the optimization of 1) the sampling pattern in k-space under MR hardware constraints and 2) image r…
Learning the sampling density in 2D SPARKLING MRI acquisition for optimized image reconstruction
Chaithya G R, Zaccharie Ramzi, Philippe Ciuciu
The SPARKLING algorithm was originally developed for accelerated 2D magnetic resonance imaging (MRI) in the compressed sensing (CS) context. It yields non-Cartesian sampling trajec…
Density Compensated Unrolled Networks for Non-Cartesian MRI Reconstruction
Zaccharie Ramzi, Jean-Luc Starck, Philippe Ciuciu
Deep neural networks have recently been thoroughly investigated as a powerful tool for MRI reconstruction. There is a lack of research, however, regarding their use for a specific…
Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction
Matthew J. Muckley, Bruno Riemenschneider, Alireza Radmanesh +20
Accelerating MRI scans is one of the principal outstanding problems in the MRI research community. Towards this goal, we hosted the second fastMRI competition targeted towards reco…
Denoising Score-Matching for Uncertainty Quantification in Inverse Problems
Zaccharie Ramzi, Benjamin Remy, Francois Lanusse +2
Deep neural networks have proven extremely efficient at solving a wide rangeof inverse problems, but most often the uncertainty on the solution they provideis hard to quantify. In…
Probabilistic Mapping of Dark Matter by Neural Score Matching
Benjamin Remy, Francois Lanusse, Zaccharie Ramzi +3
The Dark Matter present in the Large-Scale Structure of the Universe is invisible, but its presence can be inferred through the small gravitational lensing effect it has on the ima…