In this paper we introduce a novel application of the diffusion tensor for anisotropic image processing. The Anisotropic Contour Completion (ACC) we suggest consists in extending the characteristic function of the open curve by means of a degenerated diffusion tensor that prevents any diffusion in the normal direction. We show that ACC is equivalent to a dilation with a continuous elliptic stru...

Introduction Diffusion tensor imaging (DTI) is a powerful technique for the noninvasive characterization of the microstructure of normal and pathological tissue. However, it is typically performed with echo-planar imaging (EPI) and is thus vulnerable to spatial and temporal variations of the static magnetic field (B0) caused by susceptibility effects near air/tissue interfaces, eddy currents in...

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy TENSOR BASED REPRESENTATION AND ANALYSIS OF DIFFUSION-WEIGHTED MAGNETIC RESONANCE IMAGES By Angelos Barmpoutis May 2009 Chair: Baba C. Vemuri Major: Computer Engineering Cartesian tensor bases have been widely used to model spherical fun...

Background Cardiac motion is a crucial problem in in vivo diffusion tensor imaging (DTI) of the human heart. Despite its importance, the effects of cardiac motion on diffusion tensor parameters of the human heart in vivo have not been well established, mainly because of large signal loss. Recently, an efficient method was proposed that acquires cardiac diffusion weighted (DW) images at differen...

BACKGROUND AND PURPOSE Disruption of the cytoskeletal network and axonal membranes characterizes diffuse axonal injury (DAI) in the first few hours after traumatic brain injury. Histologic abnormalities seen in DAI hypothetically decrease the diffusion along axons and increase the diffusion in directions perpendicular to them. DAI therefore is hypothetically associated in the short term with de...

A new method for diffusion tensor MRI (DT-MRI) regularization is presented that relies on graph diffusion. We represent a DT image using a weighted graph, where the weights of edges are functions of the geodesic distances between tensors. Diffusion across this graph with time is captured by the heat-equation, and the solution, i.e. the heat kernel, is found by exponentiating the Laplacian eigen...

This paper discusses registration of diffusion tensor (DT) MRIs (magnetic resonance images). An existing method for registration of 3D intensity images, the multi-resolution elastic matching algorithm, [1-3], is adapted to work with this new data type. A method is described for extracting the appropriate reorientation of DTs to accompany warps of the image from the local displacement field. Fur...

BACKGROUND AND PURPOSE Diffusion tensor imaging measures the proton diffusivity and preferential orientation of the diffusion tensor. X-linked adrenoleukodystrophy is a demyelinating disease for which therapy depends on the onset and extension of demyelination. We investigated the ability of diffusion tensor imaging to detect changes in the demyelinated lesions and in the normal appearing white...

1. Definitions: a. Diffusion Tensor Imaging (DTI) refers to the acquisition and reconstruction of MR images with diffusion-encoding gradients applied in a minimum of 6 non-collinear directions, followed by voxel-wise calculation of the tensor representation of a 3D Gaussian model of the diffusion profile and subsequent mapping of any number of tensor parameters. Most commonly these would includ...

The tensors produced by diffusion tensor magnetic resonance imaging (DTMRI) represent the covariance in a Brownian motion model of water diffusion. Under this physical interpretation, diffusion tensors are required to be symmetric, positive-definite. However, current approaches to statistical analysis of diffusion tensor data, which treat the tensors as linear entities, do not take this positiv...