Among many dimensional and dimensionless amplitude parameters, Kurtosis (4-th normalized moment of probability density function) is recognized to be the sensitive good parameter for machine diagnosis. Kurtosis has a value of 3.0 under normal condition and the value generally goes up as the deterioration proceeds. But there are cases that kurtosis value goes up and then goes down when damages in...

Exact low-resolution brain electromagnetic tomography (eLORETA) is a technique for three-dimensional representation of the distribution of sources of electrical activity in the brain. Kurtosis analysis allows for identification of spiky activity in the brain. To evaluate the reliability of eLORETA kurtosis analysis, the results of the analysis were compared with those of equivalent current dipo...

It is often suggested that efficient neural codes for natural visual information should be 'sparse'. However, the term 'sparse' has been used in two different ways--firstly to describe codes in which few neurons are active at any time ('population sparseness'), and secondly to describe codes in which each neuron's lifetime response distribution has high kurtosis ('lifetime sparseness'). Althoug...

Synopsis We compute the higher-order statistics of the 3D spin displacement probability distributions measured with mean apparent propagator (MAP) MRI and quantify microstructural tissue parameters such as the mean kurtosis (MK), axial kurtosis (K ), radial kurtosis (K ) and kurtosis fractional anisotropy (FA ). This extension of the family of MAP tissue parameters provides a direct link betwee...

Introduction Diffusion kurtosis tensor imaging provides additional information compared with diffusion tensor imaging [1,2]. Solving the kurtosis tensor, however, requires measurements in at least 15 diffusion-encoding directions as well as measurements with at least three or more b-values in each of these directions [2]. This leads to scanning times in the order of 6-10 minutes, which is often...

Currently, it appears that the best method for non-Gaussianity detection in the Cosmic Microwave Background (CMB) consists in calculating the kurtosis of the wavelet coefficients. We know that wavelet-kurtosis outperforms other methods such as the bispectrum, the genus, ridgelet-kurtosis and curvelet-kurtosis on an empirical basis, but relatively few studies have compared other transform-based ...

Background Diffusion tensor imaging (DTI), a gaussian anisotropic diffusion model, provides mean diffusivity (MD) and fractional anisotropy (FA) metrics that describe diffusion in brain tissue (white and gray matter). However, the widely recognized non-gaussian diffusion behavior in tissue has motivated higher order schemes (q-ball, HARDI, DSI) to accurately describe the tissue structure. In ge...

BACKGROUND AND PURPOSE Motor impairment is the most common deficit after stroke. Our aim was to evaluate whether diffusional kurtosis imaging can detect corticospinal tract microstructural changes in the acute phase for patients with first-ever ischemic stroke and motor impairment and to assess the correlations between diffusional kurtosis imaging-derived diffusion metrics for the corticospinal...

BACKGROUND AND PURPOSE Temporal lobe epilepsy is associated with regional abnormalities in tissue microstructure, as demonstrated by DTI. However, the full extent of these abnormalities has not yet been defined because DTI conveys only a fraction of the information potentially accessible with diffusion MR imaging. In this study, we assessed the added value of diffusional kurtosis imaging, an ex...

Purpose To evaluate the clinical utility of diffusion kurtosis tensor imaging in the characterization of cerebral glioma and investigate correlations between diffusion and kurtosis metrics with tumor cellularity. Materials and Methods A group of 163 patients (age: 40.5 ± 11.5 years) diagnosed with cerebral glioma underwent diffusion kurtosis tensor imaging with a 3 T scanner. Diffusion and kurt...