In this paper, we discuss matching of diffusion tensor (DT) MRIs of the human brain. Issues concerned with matching and transforming these complex images are discussed. A number of similarity measures are proposed, based on indices derived from the DT, the DT itself and the DT deviatoric. Each measure is used to drive an elastic matching algorithm applied to the task of registration of 3D image...

We derive herein first and second-order differential operators for detecting structure in diffusion tensor MRI (DTI). Unlike existing methods, we are able to generate full first and second-order differentials without dimensionality reduction and while respecting the underlying manifold of the data. Further, we extend corner and curvature feature detectors to DTI using our differential operators...

BACKGROUND AND PURPOSE: MR diffusion tensor imaging permits detailed visualization of white matter fiber tracts. This technique, unlike T2−weighted imaging, also provides information about fiber direction. We present normal white matter fiber tract anatomy at high−resolution using line scan diffusion tensor imaging. METHODS: Diffusion tensor images in axial, coronal and sagittal sections coveri...

conclusion vr reconstruction for both single-direction images and sushi using dti25 raw data provides excellent 3d displays of the peripheral nerves in the wrist region. sushi post-processing is a useful denoising tool because it automatically reduces the majority of isotropic object noise. results single-direction vr reconstruction clearly showed the nerves for both dti6 and dti25 but with obv...

This paper presents a new method for warping of diffusion tensor fields. The proper reorientation of a tensor field requires knowledge of the underlying fiber orientation, which is not known a priori. Accordingly, a probabilistic representation of the fiber direction is adopted and used in a Procrustean estimation of the rotational component of the warping field. The estimated rotational compon...

We present a unified framework for interpolation and regularisation of scalarand tensor-valued images. This framework is based on elliptic partial differential equations (PDEs) and allows rotationally invariant models. Since it does not require a regular grid, it can also be used for tensor-valued scattered data interpolation and for tensor field inpainting. By choosing suitable differential op...

A Wideband diffusion tensor imaging is successfully performed to acquire two images in one single excitation. 2-slices are excited/acquired simultaneously using 2D Wideband modified pulse-gradient spin-echo sequence. The calculated diffusion tensors of the grapefruit are clearly displayed on the eigenvector map, and proven to be correct. The result of this study directly indicates a reduction o...

Magnetic resonance electrical impedance tomography (MREIT) is an emerging method to visualize electrical conductivity and/or current density images at low frequencies (below 1 KHz). Injecting currents into an imaging object, one component of the induced magnetic flux density is acquired using an MRI scanner for isotropic conductivity image reconstructions. Diffusion tensor MRI (DT-MRI) measures...

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...

The purpose of this study is to develop a noninvasive quantitative imaging scheme to assess the functional microanatomy of dog brain using high resolution diffusion tensor imaging (DTI) at 7-Tesla (T) magnetic resonance imaging (MRI) scanner. Diffusion weighted images (DWIs) along 25 diffusion-encoding directions, combined with T2 weighted images, were acquired using the standard spin-echo diff...