Outlier Detection for High B-Value Diffusion Data

Kerstin Pannek¹, David Raffelt², Christopher Bell¹, Jane Mathias³, Stephen Rose¹

Diffusion weighted images are prone to artefacts caused by physiological noise. Existing model based approaches for voxel-wise identification of such artefacts rely on the diffusion tensor model, which is problematic in crossing fibre areas and at higher b-values required for high angular resolution diffusion imaging. We developed a voxel-wise identification method based on a higher order model of diffusion, and compared outlier probability maps obtained using the tensor model with those obtained using a higher order model in a cohort of 103 healthy participants.