MRI image reconstruction from undersampled data using adversarially trained generative neural network

摘要

A method of magnetic resonance imaging acquires undersampled MRI data and generates by an adversarially trained generative neural network MRI data having higher quality without using any fully-sampled data as a ground truth. The generative neural network is adversarially trained using a discriminative neural network that distinguishes between undersampled MRI training data and candidate undersampled MRI training data produced by applying an MRI measurement function containing an undersampling mask to generated MRI training data produced by the generative neural network from the undersampled MRI training data.