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

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.

8 pages, 3 figures, presented as an oral to the 2021 ISMRM conference