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Abstract #3095

A physically-constrained model for diffusion kurtosis imaging

Darryl McClymont1, Irvin Teh1, Hannah Whittington1, Vicente Grau2, and Jurgen Schneider1

1Division of Cardiovascular Medicine, University of Oxford, Oxford, United Kingdom, 2Department of Engineering Science, University of Oxford, Oxford, United Kingdom

Diffusion kurtosis imaging provides higher-order information about diffusion. However, the quadratic term in the diffusion kurtosis model produces undesirable behaviour at high b-values as a result of the negative tails of the diffusivity distribution. A truncated normal distribution has been proposed to address this in one dimension. This work extends this concept to a multivariate truncated normal distribution, and extends the range of b-values over which kurtosis can be estimated. The proposed model is fit to diffusion data from rat hearts, and yields kurtosis values that are consistent with the DKI model.

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