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A deep residual learning convolutional neural network (DRL-CNN) was applied to improve image quality and speed up the reconstruction of compressed sensing magnetic resonance imaging. The reconstruction performances of the proposed method was compared with iterative reconstruction methods.

Reconstruction of Compressed-sensing MR Imaging Using Deep Residual Learning in the Image Domain