XPDNet for MRI Reconstruction: an application to the 2020 fastMRI challenge
2020-10-15Code Available1· sign in to hype
Zaccharie Ramzi, Philippe Ciuciu, Jean-Luc Starck
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ReproduceCode
- github.com/zaccharieramzi/fastmri-reproducible-benchmarkOfficialIn papertf★ 161
- github.com/wdika/mridcpytorch★ 40
- github.com/f78bono/deep-cine-cardiac-mripytorch★ 18
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.
Tasks
Benchmark Results
| Dataset | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| fastMRI Brain 4x | XPDNet | SSIM | 0.96 | — | Unverified |
| fastMRI Brain 8x | XPDNet | SSIM | 0.94 | — | Unverified |
| fastMRI Knee 4x | XPDNet | SSIM | 0.93 | — | Unverified |
| fastMRI Knee 8x | XPDNet | SSIM | 0.89 | — | Unverified |