Diffusion MRI (dMRI) measurements are used for inferring the microstructural properties of
white matter and to reconstruct fiber pathways. Very often voxels contain complex fiber …

We introduce an algorithm for diffusion weighted magnetic resonance imaging data
enhancement based on structural adaptive smoothing in both voxel space and diffusion …

We present a novel multi-shell position-orientation adaptive smoothing (msPOAS) method
for diffusion weighted magnetic resonance data. Smoothing in voxel and diffusion gradient …

Diffusion tensor imaging is widely used in research and clinical applications, but this
modality is highly sensitive to artefacts. We developed an easy‐to‐implement extension of …

Noise is a common issue for all magnetic resonance imaging (MRI) techniques such as
diffusion MRI and obviously leads to variability of the estimates in any model describing the …

We consider mixtures of general angular central Gaussian distributions as models for
multimodal directional data. We prove consistency of the maximum‐likelihood estimates of …

Our interest in neuroimaging started some 20 years ago, initiated by talks given by Fred
Godtliebsen (UiT, Tromsø, Norway) and by Fridhjof Kruggel (Max-Planck-Institute of …

Diffusion Kurtosis Imaging (DKI) is more sensitive to microstructural differences and can be
related to more specific micro-scale metrics (eg, intra-axonal volume fraction) than diffusion …

We consider Bayesian analysis on high‐dimensional spheres with angular central Gaussian
priors. These priors model antipodally symmetric directional data, are easily defined in …

This paper presents a novel family of linear transforms that can be applied to data collected
from the surface of a 2-sphere in three-dimensional Fourier space. This family of transforms …