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.
Keywords