Image quality improvement in magnetic resonance imaging using machine learning reconstruction

Abstract

A method, system, processing circuitry, and computer program product for processing images, including, by performing the steps of: receiving an input image generated using a first set of acquired k-space data including undersampled k-space data; dealiasing the input image to produce a dealiased image; modifying the dealiased image using a first data consistency layer to increase a first data consistency between the dealiased image and an acquired data source thereby producing a first increased data consistency image; and modifying, using a second data consistency layer that receives the undersampled k-space data, the first increased data consistency image to produce a second increased data consistency image in which the second increased data consistency image is constrained to be based on at least a portion of the undersampled k-space data, where the first and second data consistency layers are different from each other.