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Abstract #1383

Pearson Set of Distributions as Improved Signal Model for Diffusion Kurtosis Imaging

Dirk H. J. Poot1, Arjan J. den Dekker2, Jan Sijbers1

1Visionlab, University of Antwerp, Antwerp, Belgium; 2Delft Center for Systems and Control, TUDelft, Delft, Netherlands


This work explains a new model which includes the kurtosis of the diffusion process in the model of the recorded diffusion weighted images. This new model is based on the Pearson set of statistical distributions. Compared to the traditional Taylor approximation based model of the diffusion weighted images, this model provides more realistic and accurate predictions of the magnitude of the diffusion weighted images, especially for large b-values. To be able to estimate the kurtosis, these large b-values are needed. Therefore, this improved model is relevant for the estimation of kurtosis measures from diffusion weighted images.