Papers › XPDNet for MRI Reconstruction: an application to the 2020 fastMRI challenge
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 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.
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Code
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84d5c6962fcc37f2 · report
Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| MRI Reconstruction | fastMRI Brain 4x | XPDNet | PSNR | 41.3 | #2 of 2 | Archive leaderboard | report |
| MRI Reconstruction | fastMRI Brain 4x | XPDNet | SSIM | 0.9581 | #2 of 2 | Archive leaderboard | report |
| MRI Reconstruction | fastMRI Brain 8x | XPDNet | PSNR | 38.1 | #2 of 2 | Archive leaderboard | report |
| MRI Reconstruction | fastMRI Brain 8x | XPDNet | SSIM | 0.9408 | #2 of 2 | Archive leaderboard | report |
| MRI Reconstruction | fastMRI Knee 4x | XPDNet | PSNR | 40.2 | #2 of 2 | Archive leaderboard | report |
| MRI Reconstruction | fastMRI Knee 4x | XPDNet | SSIM | 0.9287 | #2 of 2 | Archive leaderboard | report |
| MRI Reconstruction | fastMRI Knee 8x | XPDNet | PSNR | 37.2 | #4 of 4 | Archive leaderboard | report |
| MRI Reconstruction | fastMRI Knee 8x | XPDNet | SSIM | 0.8893 | #4 of 4 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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