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3 months ago
XPDNet for MRI Reconstruction: an application to the 2020 fastMRI challenge
Zaccharie Ramzi Philippe Ciuciu Jean-Luc Starck

Abstract
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 from MRI reconstruction and computer vision. We show that this network can achieve state-of-the-art reconstruction results, as shown by its ranking of second in the fastMRI 2020 challenge.
Code Repositories
zaccharieramzi/fastmri-reproducible-benchmark
Official
tf
Mentioned in GitHub
wdika/mridc
pytorch
Mentioned in GitHub
f78bono/deep-cine-cardiac-mri
pytorch
Mentioned in GitHub
Benchmarks
| Benchmark | Methodology | Metrics |
|---|---|---|
| mri-reconstruction-on-fastmri-brain-4x | XPDNet | PSNR: 41.3 SSIM: 0.9581 |
| mri-reconstruction-on-fastmri-brain-8x | XPDNet | PSNR: 38.1 SSIM: 0.9408 |
| mri-reconstruction-on-fastmri-knee-4x | XPDNet | PSNR: 40.2 SSIM: 0.9287 |
| mri-reconstruction-on-fastmri-knee-8x | XPDNet | PSNR: 37.2 SSIM: 0.8893 |
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