Denoising diffusion models for plug-and-play mr image restoration/reconstruction

A system for diffusion plug and play (PnP) image reconstruction of magnetic resonance (MR) data, the system comprising:

• a medical imaging device configured to acquire MR data;
• a memory configured to store a model configured to reconstruct an MR images when input MR data, wherein the model is configured to iteratively refine the MR data using diffusion PnP, wherein for each step of the iterative process, a pretrained diffusion model is used to remove noise to predict a next state of the iterative process and measurement data is incorporated by solving a data proximal subproblem, the measurement data applied to the next state to ensure consistency;
• and
• a processor configured to reconstruct and/or restore the MR image from the MR data using the model.

A method for diffusion plug and play (PnP) image restoration of medical imaging data, comprising:

• acquiring medical imaging data;
• iteratively restoring the medical imaging data using a diffusion PnP model that includes measurement during reverse diffusion steps, wherein the measurement is carried out after a correction step that accounts for an inaccurate estimation resulting from computing a proximal solution;
• and
• outputting a restored image.