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Effect Size Comparison for Gaussian and Rician Modelling within fMRI Data

Book Contribution - Book Chapter Conference Contribution

It has been argued that due to the bias at low SNR,
the Gaussian approach is unsuitable for modelling Rician fMRI
data. As a result several estimators incorporating the Rician
nature of the data have been proposed to measure the signal
as accurately as possible.
However, within fMRI the main objective is not to measure
the signal, but rather to measure changes within the signal. As
an increasing function of the signal, the mean can be used for
this purpose as well. In this paper it is argued that, due to its
lower variance, the sample average is a more suitable tool to
detect changes in the amplitude than several conventional Rician
parameter estimators at those SNR values common within fMRI
measurements.
While the interpretation is slightly different, this Rician
mean-based approach is essentially equivalent to the Gaussian
approach. Despite its bias, the Gaussian approach is therefore
preferable within fMRI analysis.
Book: 2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA)
Number of pages: 5
ISBN:978-1-5386-3392-2
Keywords:Rice distribution, fMRI, Effect size, Rician distribution
Authors:International
Accessibility:Closed