Babak A. Ardekani1,2, Ali Tabesh, 1,3, Jens H. Jensen3, Joseph A. Helpern, 1,3, Alvin Bachman1, Howard Kushner4
1Center for Advanced Brain Imaging, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, United States; 2Department of Psychiatry, New York University School of Medicine, New York, United States; 3Department of Radiology, New York University School of Medicine, New York, NY, United States; 4Statistical Sciences and Research Division, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, United States
In diffusional kurtosis imaging (DKI), the non-Gaussian nature of water diffusion in biological tissue is characterized by a kurtosis parameter, estimated in every voxel from a set of diffusion-weighted image acquisitions. This paper presents an improved method for estimating the kurtosis parameter in DKI. The specific contributions of this paper are twofold. (1) We propose a new method for imposing a positive-definiteness constraint on the fourth order tensor estimates and show its particular importance in DKI. (2) We propose using Mardias multivariate definition of kurtosis to characterize non-Gaussian diffusion, as opposed to mean univariate kurtosis used in previous publications.