Post-processing of diffusion-weighted MR data lowers the accuracy of the weighted linear least squares estimator
Jelle Veraart 1 and Jan Sijbers 1
Vision Lab, University of Antwerp, Antwerp,
For clinically relevant SNR values (SNR>2), the weighted
linear least squares estimator is theoretically expected
to be as accurate as advanced estimators that
incorporate prior knowledge of the data distribution in
the estimation of DTI/DKI model parameters. However, one
must bear in mind that the high accuracy vanishes if
magnitude operations are applied prior to model fitting.
After magnitude operations, which are generally included
in the diffusion MRI processing pipeline, the prior
knowledge of the noise parameter becomes a must in order
to define an unbiased estimator.
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