NC-PDNet: a Density-Compensated Unrolled Network for 2D and 3D non-Cartesian MRI Reconstruction
Deep Learning has become a very promising avenue for magnetic resonance image (MRI) reconstruction.…
Category: publications_zr
Z. Ramzi’s publications
Density Compensated Unrolled Networks for Non-Cartesian MRI Reconstruction
Deep neural networks have recently been thoroughly investigated as a powerful tool for MRI…
State-of-the-art Machine Learning MRI Reconstruction in 2020: Results of the Second fastMRI Challenge
Accelerating MRI scans is one of the principal outstanding problems in the MRI research…
Probabilistic Mapping of Dark Matter by Neural Score Matching
The Dark Matter present in the Large-Scale Structure of the Universe is invisible, but…
XPDNet for MRI Reconstruction: an Application to the fastMRI 2020 Brain Challenge
We present a modular cross-domain neural network the XPDNet and its application to the…
Denoising Score-Matching for Uncertainty Quantification in Inverse Problems
Deep neural networks have proven extremely efficient at solving a wide range of inverse…
Wavelets in the Deep Learning Era
Sparsity based methods, such as wavelets, have been state-of-the-art for more than 20 years…
Benchmarking Deep Nets MRI Reconstruction Models on the FastMRI Publicly Available Dataset
The MRI reconstruction field lacked a proper data set that allowed for reproducible…
Benchmarking proximal methods acceleration enhancements for CS-acquired MR image analysis reconstruction
Reference: Z. Ramzi, P. Ciuciu and J.-L. Starck. “Benchmarking proximal methods acceleration enhancements for CS-acquired MR image…
PySAP: Python Sparse Data Analysis Package for Multidisciplinary Image Processing
Authors: S. Farrens, A. Grigis, L. El Gueddari, Z. Ramzi, Chaithya G. R.,…