Segmented diffusion imaging with iterative motion corrected reconstruction (SEDIMENT) is studied at 7T for self-navigated multi-shot DWI reconstruction including rigid in-plane motion correction. Motion-corrupted datasets contain intra-shot motion corrupted data with imperfect diffusion-sensitizing gradient reversal, which have to be identified and removed. The iterative SEDIMENT framework is evaluated in-vivo in conjunction with tailored data rejection strategies to detect corrupted shot datasets and generally improve convergence. The proposed algorithm provides high-quality multi-shot DWI and DTI reconstructions in the presence of gross motion allowing for efficient navigator-free DWI acquisition schemes.
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