We performed parallel MRI reconstruction from under-sampled k-space data using the Multi-Domain Neumann Network with Sensitivity Maps. The Neumann network solves the inverse problem with recursive neural networks taking account into the forward model. We adapt the Neumann network with the coil sensitivity estimation and k-space data regurlaization to take account into MR physical models. Our proposed method shows uppressed image artifacts and enhanced spatial resolution compared with GRAPPA, U-Net and Neumann network.
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