Fractional anisotropy (FA), defined as the distance of a diffusion tensor from its closest isotropic tensor, has been extensively studied as quantitative anisotropy measure for diffusion tensor magnetic resonance images (DT-MRI). It has been used to reveal the white matter profile of brain images, as guiding feature for seeding and stopping in fiber tractography and for the diagnosis and assess...

Image registration is a common image processing task, and therefore, many algorithms have been proposed and described to carry it out for different image modalities. However, the application of these algorithms to diffusion tensor imaging is not straightforward due to the special features of this kind of data, where a tensor is defined at each voxel. The information provided by the diffusion te...

The regularized iterative reconstruction of the tensor field in diffusion tensor tomography magnetic resonance imaging was investigated. The total variation constraints on eigenvalue and tensor component images of the diffusion tensor were explored. A computer generated phantom was used to simulate the diffusion tensor in a cardiac MRI study in which the diffusion model depended upon the fiber ...

This paper investigates the iterative reconstruction of tensor fields in diffusion tensor magnetic resonance imaging (MRI). The gradient constraints on eigenvalue and tensor component images of the diffusion tensor were exploited. A computer-generated phantom was used in order to simulate the diffusion tensor in a cardiac MRI study with a diffusion model that depends on the fiber structure of t...

We consider the problem of segmenting fiber bundles in diffusion tensor images. We cast this problem as a manifold clustering problem in which different fiber bundles correspond to different submanifolds of the space of diffusion tensors. We first learn a local representation of the diffusion tensor data using a generalization of the locally linear embedding (LLE) algorithm from Euclidean to di...

While mouse brain development has been extensively studied using histology, quantitative characterization of morphological changes is still a challenging task. This paper presents how developing brain structures can be quantitatively characterized with magnetic resonance diffusion tensor microimaging coupled with techniques of computational anatomy. High resolution diffusion tensor images of ex...

Two- and three-dimensional (3D) white matter atlases were created on the basis of high-spatial-resolution diffusion tensor magnetic resonance (MR) imaging and 3D tract reconstruction. The 3D trajectories of 17 prominent white matter tracts could be reconstructed and depicted. Tracts were superimposed on coregistered anatomic MR images to parcel the white matter. These parcellation maps were the...

In this chapter, we introduce the problem of registering diffusion tensor magnetic resonance (DT-MR) images. The registration task for these images is made challenging by the orientational information they contain, which is affected by the registration transformation. This information about orientation and other aspects of the diffusion tensor are exploited in the development of similarity meas...

INTRODUCTION Diffusion tensor MRI (DT-MRI) provides a discrete representation of the diffusion tensor field ofwater in living tissues. A graphical means to display the diffusion tensor field, '[\]is to construct diffusion ellipsoid maps or images (1). Moreover, from the diffusion tensor field, one can infer the fiber-tract direction field in some anisotropic tissues (1). 1n white matter and ske...