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

2020/10/15 by Ramzi, Zaccharie, Ciuciu, Philippe, Starck, Jean-Luc
#Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Physical sciences #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Medical Physics (physics.med-ph) #electronic engineering #information engineering

paper · doi:10.48550/arxiv.2010.07290

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.

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