We introduce and validate an artificial intelligence (AI)-accelerated multi-shot echo-planar imaging (msEPI)-based method that provides T1w, T2w, T * 2 , T2-FLAIR, and DWI images with high SNR, high tissue contrast, low specific absorption rates (SAR), and minimal distortion in 2 minutes.
Methods:The rapid imaging technique combines a novel machine learning (ML) scheme to limit g-factor noise amplification and improve SNR, a magnetization transfer preparation module to provide clinically desirable contrast, and high per-shot EPI undersampling factors to reduce distortion. The ML training and image reconstruction incorporates a tunable parameter for controlling the level of denoising/smoothness. The performance of the reconstruction method is evaluated across various acceleration factors, contrasts, and SNR conditions. The 2-minute protocol is directly compared to a 10-minute clinical reference protocol through deployment in a clinical setting, where five representative cases with pathology are examined. Results: Optimization of custom msEPI sequences and protocols was performed to balance acquisition efficiency and image quality compared to the five-fold longer clinical reference. Training data from 16 healthy subjects across multiple contrasts and orientations were used to produce ML networks at various