Score-based Generative Priors Guided Model-driven Network for MRI Reconstruction

arXiv:2405.02958v1 Announce Type: new
Abstract: Score matching with Langevin dynamics (SMLD) method has been successfully applied to accelerated MRI. However, the hyperparameters in the sampling process require subtle tuning, otherwise the results can be severely corrupted by hallucination artifacts, particularly with out-of-distribution test data. In this study, we propose a novel workflow in which SMLD results are regarded as additional priors to guide model-driven network training. First, we adopted a pretrained score network to obtain samples as preliminary guidance images …

abstract arxiv cs.cv data distribution dynamics generative hallucination however mri network novel process results sampling study test type