Introduction: In 2003 Ozarslan et al introduced Generalised DTI, and showed how the data from a diffusion MRI experiment can be described by a higher rank tensor [1]. In 2005 the same authors proposed two generalised anisotropy metrics that can be calculated from any n-rank tensor [2]. The normalisation of these metrics is achieved by using a scaling function, with parameters that can be change...

Diffusion tensor reconstruction is made possible through the acquisition of several diffusion weighted images, each corresponding to a given sampling direction in the q-space. In this study, we address the question of sampling efficiency, and show that in case we have some prior knowledge on the diffusion characteristics, we may be able to adapt the sampling directions for better reconstruction...

Introduction Understanding early human brain development is of great clinical importance, as many neurological and neurobehavioral disorders have their origin in early structural and functional brain development. With conventional magnetic resonance imaging we have been able to delineate macroscopically early developmental events such as myelination and gyral development. Diffusion tensor imagi...

The aim of the present study was to present a novel non-local mean (NLM) method to denoise diffusion tensor imaging (DTI) data in the tensor space. Compared with the original NLM method, which uses intensity similarity to weigh the voxel, the proposed method weighs the voxel using tensor similarity measures in the diffusion tensor space. Euclidean distance with rotational invariance, and Rieman...

There has been substantial interest in the development of methods for processing diffusion tensor fields, taking into account the non-Euclidean nature of the tensor space. In this paper, we generalise Procrustes analysis to weighted Procrustes analysis for diffusion tensor smoothing, interpolation, regularisation and segmentation in which an arbitrary number of tensors can be processed efficien...

In this paper we present a mathematical and numerical framework for a procedure of imaging anisotropic electrical conductivity tensor by integrating magneto-acoutic tomography with data acquired from diffusion tensor imaging. Magneto-acoustic Tomography with Magnetic Induction (MAT-MI) is a hybrid, non-invasive medical imaging technique to produce conductivity images with improved spatial resol...

Diffusion tensor imaging (DTI) has become a powerful tool for analyzing the structure of white matter. We have proposed a method for detecting nerve fiber bundles in white matter using diffusion tensor images and have applied the method to in vivo brain measurements. Although there are many methods to investigate the connectivity of white matter that are based on principal eigenvector or full t...

BACKGROUND Histological behavior of glioblastoma multiforme suggests it would benefit more from a global rather than regional evaluation. A global (whole-brain) calculation of diffusion tensor imaging (DTI) derived tensor metrics offers a valid method to detect the integrity of white matter structures without missing infiltrated brain areas not seen in conventional sequences. In this study we c...