Parallel imaging reconstruction using iterative CNN-based denoising in image domain

We propose an iterative reconstruction method of parallel imaging using convolutional neural network (CNN)-based denoising in the image domain and data-consistency processing in k-space. The proposed method reduces the noise and artifacts of a reconstructed image compared with the iterative method using sparsity of wavelet transform, suggesting that using CNN-based denoising in iterative reconstruction is effective in reducing noise in parallel imaging.