Motivation: Joint motion/image optimization in aligned reconstruction can be computationally inefficient; scout-based method uses additionally acquired data to accelerate calculation, which may also be motion-corrupted. Goal(s): To develop a 3D motion correction method which takes the advantages of both self-navigation and fast calculation. Approach: A 3D radial acquisition and a multi-temporal, multi-spatial resolution scheme was used to formulate convex motion optimization subproblem. The temporal continuity of motion was introduced to constrain the resulted motion patterns. A motion-informed CS reconstruction was performed for accelerated image reconstruction. Results: The proposed method achieved joint optimization in 2 joint iterations at time resolution of 0.7s with 7.5x undersampling. Impact: A flexible and time-efficient method based on aligned reconstruction framework was developed for rigid-body motion correction in accelerated brain MRI, which may be beneficial to the exams of clinical uncooperative patients as well as brain MRI research community.
Li et al. (Tue,) studied this question.