313 citations · 375 across the 15 of their papers we have counts for
4 papers · 1 filter
Is good old GRAPPA dead?
Zaccharie Ramzi, Alexandre Vignaud, Jean-Luc Starck +1
We perform a qualitative analysis of performance of XPDNet, a state-of-the-art deep learning approach for MRI reconstruction, compared to GRAPPA, a classical approach. We do this i…
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…
XPDNet for MRI Reconstruction: an application to the 2020 fastMRI challenge
Zaccharie Ramzi, Philippe Ciuciu, Jean-Luc Starck
We present a new neural network, the XPDNet, for MRI reconstruction from periodically under-sampled multi-coil data. We inform the design of this network by taking best practices f…