In order to describe anisotropy in image processing models or physical measurements, matrix fields are a suitable choice. In diffusion tensor magnetic resonance imaging (DT-MRI), for example, information about the diffusive properties of water molecules is captured in symmetric positive definite matrices. The corresponding matrix field reflects the structure of the tissue under examination. Rec...

Acquisition, analysis, and visualization of diffusion tensor magnetic resonance imaging (DT-MRI) is still an evolving technology. This article reviews the fundamentals of the data acquisition process and the pipeline leading to visual results that are interpretable by physicians in their clinical practice. The limitations of common approaches for visualizing the retrieved data are discussed and...

A new method for diffusion tensor (DT) image regularization is presented that relies on heat diffusion on discrete structures. We represent a DT image using a weighted undirected graph, where the weights of the edges are determined from the geometry of the white matter fiber pathways. Diffusion across this weighted graph is captured by the heat equation, and the solution, i.e. the heat kernel, ...

General fluid-type intelligence (gF) reflects abstract reasoning and problem solving abilities, and is an important predictor for lifetime trajectories of cognition, and physical and mental health. Structural and functional neuroimaging studies have demonstrated the role of parieto-frontal gray matter, but the white matter (WM) underpinnings of gF and the contribution of individual gF component...

OBJECTIVE The authors assessed whether brain changes detected by diffusion tensor (DT) MRI can improve the understanding of structural damage in Alzheimer's disease (AD) and are associated with different risks of conversion to AD in amnestic mild cognitive impairment (aMCI). METHODS Twenty-one aMCI patients, 21 AD patients and 20 healthy subjects underwent conventional and DT MRI at baseline....

We assessed abnormalities within the principal brain resting state networks (RSNs) in patients with Leber's hereditary optic neuropathy (LHON) to define whether functional abnormalities in this disease are limited to the visual system or, conversely, tend to be more diffuse. We also defined the structural substrates of fMRI changes using a connectivity-based analysis of diffusion tensor (DT) MR...

Registration of diffusion tensor (DT) images is indispensible, especially in white-matter studies involving a significant amount of data. This task is however faced with challenging issues such as the generally low SNR of diffusion-weighted images and the relatively high complexity of tensor representation. To improve the accuracy of DT image registration, we design an attribute vector that enc...

G. K. Rohde, S. Pajevic, C. Pierpaoli, P. J. Basser National Institutes of Health, Bethesda, Maryland, United States SYNOPSIS: With the advent of new MR imaging modalities such as DT-MRI, MRA, and CSI, demand for image registration procedures capable of dealing with multi-channel image data has increased. A novel method based on multivariate linear correlation is proposed to align two multi-cha...

This paper aims to identify the minimum requirements for an accurate model of the diffusion MR signal in white matter of the brain. We construct a taxonomy of multi-compartment models of white matter from combinations of simple models for the intra- and the extra-axonal spaces. We devise a new diffusion MRI protocol that provides measurements with a wide range of imaging parameters for diffusio...

BACKGROUND AND PURPOSE Cerebral small vessel disease is the most common cause of vascular dementia. Interest in using MRI parameters as surrogate markers of disease to assess therapies is increasing. In patients with symptomatic sporadic small vessel disease, we determined which MRI parameters best correlated with cognitive function on cross-sectional analysis and which changed over a period of...