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arXiv · 1902.10815

Generalizing Deep Learning MRI Reconstruction across Different Domains

Cheng Ouyang·Jo Schlemper·Carlo Biffi·Gavin Seegoolam·Jose Caballero·Anthony N. Price·Joseph V. Hajnal·Daniel Rueckert
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Abstract

We look into the robustness of deep learning based MRI reconstruction when tested on unseen contrasts and organs. We then propose to generalize the network by training with large publicly-available natural image datasets with synthesized phase information to achieve high cross-domain reconstruction performance which is competitive with domain-specific training. To explain its generalization mechanism, we have also analyzed patch sets for different training datasets.

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Cheng Ouyang, Jo Schlemper, Carlo Biffi, Gavin Seegoolam, Jose Caballero, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert. 2019-01-31. Generalizing Deep Learning MRI Reconstruction across Different Domains. https://arxiv.org/abs/1902.10815

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