The bootstrap technique is an extremely powerful nonparametric statistical procedure for
determining the uncertainty in a given statistic. However, its use in diffusion tensor MRI …

Diffusion tensor magnetic resonance imaging (DT-MRI) permits the noninvasive assessment
of tissue microstructure and, with fibre-tracking algorithms, allows for the 3-D trajectories of …

A method is presented that is capable of determining more than one fiber orientation within a
single voxel in high angular resolution diffusion imaging (HARDI) data sets. This method is …

Abstract Diffusion tensor MRI (DT‐MRI) permits determination of the dominant orientation of
structured tissue within an image voxel. This has led to the development of 2D graphical …

There are conflicting opinions in the literature as to whether it is more beneficial to use a
large number of gradient sampling orientations in diffusion tensor MRI (DT‐MRI) …

A fully probabilistic framework is presented for estimating local probability density functions
on parameters of interest in a model of diffusion. This technique is applied to the estimation …

Diffusion tensor fiber tracking potentially can give information about in vivo brain
connectivity. However, this technique is difficult to validate due to the lack of a gold standard …

Bootstrap is an empirical non-parametric statistical technique based on data resampling that
has been used to quantify uncertainties of diffusion tensor MRI (DTI) parameters, useful in …

Diffusion tensor tractography based on line propagation is a promising and widely used
technique, but it is known to be sensitive to noise and the size and location of the seed …

A theoretical framework is presented for understanding the effects of noise on estimates of
the eigenvalues and eigenvectors of the diffusion tensor at moderate to high signal‐to‐noise …