Systems and methods of generating robust phase images in magnetic resonance images

A phase image correction and noise reduction system, comprising a phase image correction and noise reduction computing device, the phase image correction and noise reduction computing device comprising at least one processor in communication with at least one memory device, and the at least one processor programmed to:

• execute a neural network model for analyzing MR images, wherein the neural network model is trained with a pair of pristine images and corrupted images, wherein the corrupted images include corrupted phase information, the pristine images are the corrupted images with the corrupted phase information reduced, and target output images of the neural network model are the pristine images;
• receive MR images including corrupted phase information;
• analyze the received MR images using the neural network model;
• derive pristine phase images of the received MR images based on the analysis, wherein the pristine phase images include reduced corrupted phase information, compared to the received MR images;
• and
• output MR images based on the pristine phase images.