Diffusion kurtosis imaging (DKI) is a diffusion-weighted technique which overcomes limitations of the commonly used diffusion tensor imaging approach. This technique models non-Gaussian behaviour of water diffusion by the diffusion kurtosis tensor (KT), which can be used to provide indices of tissue heterogeneity and a better characterisation of the spatial architecture of tissue microstructure...

Depending on their molecular compositions and thermomechanical histories, extruded polyethylene (PE) films can exhibit large variations in their (usually row-nucleated) semicrystalline morphologies. In order to measure their textures quantitatively, we have optimized a procedure for the acquisition and analysis of x-ray pole figure data. Film orientation studies are often concerned with the ali...

PURPOSE Diffusion spectrum imaging (DSI) is an imaging technique that has been successfully applied to resolve white matter crossings in the human brain. However, its accuracy in complex microstructure environments has not been well characterized. THEORY AND METHODS Here we have simulated different tissue configurations, sampling schemes, and processing steps to evaluate DSI performances' und...

We provide a new, analytic kernel for scale space filtering of dMRI data. The kernel is an approximation for the Green’s function of a hypo-elliptic diffusion on the 3D rigid body motion group SE(3), for fiber enhancement in dMRI. The enhancements are described by linear scale space PDEs in the coupled space of positions and orientations embedded in SE(3). As initial condition for the evolution...

The determination of the nematic order parameter S and the orientational distribution function (ODF) from scattering data involve severe approximations. The validity of these are studied here using Monte-Carlo simulations of hard spherocylinders with an aspect ratio of 15 for varying densities in the isotropic and nematic phase. The "exact" ODF of the rods, the "exact" value of S, and the inten...

High Angular Resolution Imaging (HARDI) can better explore the complex micro-structure of white matter compared to Diffusion Tensor Imaging (DTI). Orientation Distribution Function (ODF) in HARDI is used to describe the probability of the fiber direction. There are two type definitions of the ODF, which were respectively proposed in Q-Ball Imaging (QBI) and Diffusion Spectrum Imaging (DSI). Som...

Q-ball imaging (QBI) is a high angular resolution diffusion imaging (HARDI) technique which has been proven very successful in resolving multiple intravoxel fiber orientations in MR images. The standard computation of the orientation distribution function (ODF, the probability of diffusion in a given direction) from q-ball uses linear radial projection, neglecting the change in the volume eleme...

Techniques for exploring texture-property-process relationships in various deformation processes are derived from a reduced-order model of texture evolution. The orientation distribution function (ODF) in polycrystals is represented over the Rodrigues space in a discrete form using finite element interpolation techniques. Linear programming algorithms are developed for retrieving ODFs with extr...

Q-ball imaging (QBI) is a high angular resolution diffusion imaging (HARDI) technique which has been proven very successful in resolving multiple intravoxel fiber orientations in MR images. The standard computation of the orientation distribution function (ODF, the probability of diffusion in a given direction) from q-ball data uses linear radial projection, neglecting the change in the volume ...

Introduction: High angular resolution diffusion imaging (HARDI) is a powerful extension of MRI that maps the directional diffusion of water in the brain. With more diffusion gradients and directions, fiber directions may be tracked with greater angular precision, fiber crossings can be resolved, and anisotropy measures can be derived from the full fiber orientation density function. To better r...