Abstract #3031

Automated rejection of motion-corrupted slices and optimised retrospective ghost correction for multi-shot DTI

Malte Hoffmann¹ and Stephen J Sawiak^1,2

¹Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, United Kingdom, ²Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom

DTI sequences based on EPI allow rapid acquisitions of image slices by traversing k-space lines in opposite directions following a single RF excitation. During long acquisition trains, phase errors caused by field inhomogeneity can lead to distortion. Acquiring slices in multiple shots can mitigate this effect. Motion between shots, however, results in ghosting that cannot be corrected. We show that slice-wise phase correction by entropy minimisation reduces ghosting compared to the manufacturer software (ParaVision 4.0, Bruker). Second, we propose an algorithm to automatically detect and reject slices with residual motion-induced ghosting, and validate it in a large cohort of mice.

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