Unsupervised Deep Unrolled Reconstruction Using Regularization by Denoising. (arXiv:2205.03519v2 [eess.IV] UPDATED)

Deep learning methods have been successfully used in various computer vision
tasks. Inspired by that success, deep learning has been explored in magnetic
resonance imaging (MRI) reconstruction. In particular, integrating deep
learning and model-based optimization methods has shown considerable
advantages. However, a large amount of labeled training data is typically
needed for high reconstruction quality, which is challenging for some MRI
applications. In this paper, we propose a novel reconstruction method, named
DURED-Net, that enables interpretable unsupervised learning for MR …

arxiv denoising regularization unsupervised