Motivation: Joint k-q reconstruction accelerates dMRI by exploiting shared information between diffusion directions/b-shells. However, subject motion causes artifacts in reconstruction due to inter-volume geometric inconsistency. Goal(s): To develop a motion-robust and computationally efficient joint k-q reconstruction to accelerate dMRI acquisition. Approach: We proposed a motion-robust joint k-q reconstruction method for accelerated multi-band dMRI with a multi-shell k-q model. Rigid motion parameters, motion induced phase errors, dMRI images were jointly estimated in iterative reconstruction. Variable-splitting approach was utilized to mitigate computational burden. Results: Simulation and in vivo results demonstrate that our proposed method enables robust joint k-q reconstruction in the presence of inter-volume subject motion. Impact: The developed method addresses the primary challenge in joint k-q reconstruction - subject motion, enabling robust acceleration of dMRI. This advancement facilitates translation of advanced dMRI methods to less cooperative subjects, expanding accessibility and utility of advanced dMRI in clinical setting.
Ye et al. (Tue,) studied this question.
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