Accelerating MR Reconstruction with encoding perturbations using a diffusion model

Motivation: Image distortions caused by encoding perturbations and slow MR acquisitions compromise real-time MRI-guided radiotherapy treatments.Goal(s): We aim to develop and investigate a diffusion model-based method to accelerate MR reconstruction with encoding perturbations.Approach: The diffusion model was trained by 180,670 T1-weighted brain images from a public MR dataset and nonuniform fast Fourier transform was applied to operate forward encoding process with perturbations.Results: Imaging results showed that the proposed network enabled fast MR image reconstruction with corrected geometric distortions for any subsampling patterns.Impact: The developed diffusion model to accelerate MR reconstruction with perturbations. The results demonstrated that the proposed method enabled fast distortion-corrected image reconstruction for any subsampling patterns.