MR image is easily affected by noise during the high-speed and high-resolution acquisition procedure. To effectively remove the noise and fully explore the potential of latest technique -- deep learning, in this abstract, we propose a novel MRI denoising method based on generative adversarial network. Specifically, to explore the structure similarity among neighboring slices, 3-D configuration are utilized as the basic processing unit. Residual autoencoder, combined with deconvolution operations are introduced into the generator network. The experimental results show that the proposed method achieves superior performance relative to several state-of-art methods in both noise suppression and structure preservation.
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