Distortion Correction Of BOLD Image Leveraging Cross-modality Image Translation Without Additional Scans

Motivation: State-of-the-art correction of field inhomogeneity induced image distortion in EPI based fMRI images usually depends on additional scans, which might be compromised by subject motion. Goal(s): To develop correction distortion method for BOLD image without field map or reversed phase encoding direction acquisition. Approach: We introduce a novel approach leveraging using a 3D self-attention conditional generative adversarial network (SC-GAN) and iterative registration to correct fMRI distortion with distorted fMRI and structural MRI. Results: Visual and quantitative results indicate that our method effectively correct fMRI distortion without any additional scan. The correction improves after iteration. Impact: Our approach leverage image synthesis for EPI based fMRI distortion correction, which bypass the need for additional scans, and prevent potential inaccuracy due to motion. This approach may help improve fMRI preprocessing.