Jelle Veraart1, Jan Sijbers1
1Vision Lab, University of Antwerp, Antwerp, Belgium
Many diffusion models require highly diffusion-weighted MR images, which suffer from low signal-to-noise ratio (SNR). Not only the precision of the diffusion model parameter estimators depends on the SNR, the estimators accuracy will also be affected if the Rice distribution of magnitude MR data is not accounted for. We will give a technical overview of on the one hand - the effect of the so-called Rician bias on diffusion model parameters - on the other hand some techniques, which were proposed to reduce/remove the Rician bias.