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Abstract #0467

Robust estimation of diffusion MRI metrics based on slicewise outlier detection (SOLID)

Viljami Sairanen1,2, Alexander Leemans3, and Chantal M. W. Tax4

1Medical Physics, Radiology, Helsinki University Hospital, Helsinki, Finland, 2Department of Physics, University of Helsinki, Helsinki, Finland, 3Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands, 4Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom

The accurate characterization of diffusion process with MRI is compromised by various artefacts including intensity related errors. If not appropriately accounted for, model estimates can become significantly biased resulting in erroneous metrics. Slicewise intensity errors, in particular, are often handled by excluding the entire image or slice information, or by voxelwise robust estimators that experience difficulties in partial volume regions. In this work, we describe a fast and accurate algorithm to detect slicewise outliers and a framework to incorporate this information as data uncertainty in model estimation algorithms.

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