Model-based image reconstruction for highly accelerated point spread function encoded echo planar imaging

A model-based image reconstruction (MBIR) framework is developed for highly accelerated point spread function (PSF) encoded echo planar imaging (EPI). The reconstruction accounts for known physics, and utilizes a subspace representation with local low-rank (LLR) regularization along with a variable splitting solution. Comparisons with images obtained through standard methods demonstrate considerable artifact reduction and sharpness preservation through MBIR. MBIR accommodates arbitrary sampling trajectories along the PSF-encoding dimension, enabling reconstruction of quality images from less than one minute of scan time; and we demonstrate performance boosts with nonstandard trajectories precluded by conventional reconstruction methods.