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Papers/XPDNet for MRI Reconstruction: an application to the 2020 ...

XPDNet for MRI Reconstruction: an application to the 2020 fastMRI challenge

Zaccharie Ramzi, Philippe Ciuciu, Jean-Luc Starck

2020-10-15Image ReconstructionMRI Reconstruction
PaperPDFCode(official)CodeCode

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.

Results

TaskDatasetMetricValueModel
Image ReconstructionfastMRI Knee 4xPSNR40.2XPDNet
Image ReconstructionfastMRI Knee 4xSSIM0.9287XPDNet
Image ReconstructionfastMRI Knee 8xPSNR37.2XPDNet
Image ReconstructionfastMRI Knee 8xSSIM0.8893XPDNet
Image ReconstructionfastMRI Brain 4xPSNR41.3XPDNet
Image ReconstructionfastMRI Brain 4xSSIM0.9581XPDNet
Image ReconstructionfastMRI Brain 8xPSNR38.1XPDNet
Image ReconstructionfastMRI Brain 8xSSIM0.9408XPDNet
MRI ReconstructionfastMRI Knee 4xPSNR40.2XPDNet
MRI ReconstructionfastMRI Knee 4xSSIM0.9287XPDNet
MRI ReconstructionfastMRI Knee 8xPSNR37.2XPDNet
MRI ReconstructionfastMRI Knee 8xSSIM0.8893XPDNet
MRI ReconstructionfastMRI Brain 4xPSNR41.3XPDNet
MRI ReconstructionfastMRI Brain 4xSSIM0.9581XPDNet
MRI ReconstructionfastMRI Brain 8xPSNR38.1XPDNet
MRI ReconstructionfastMRI Brain 8xSSIM0.9408XPDNet

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