Results 51 to 60 of about 389,778 (240)

Improved reproducibility of diffusion kurtosis imaging using regularized non-linear optimization informed by artificial neural networks [PDF]

arXiv, 2022
Diffusion kurtosis imaging is an extension of diffusion tensor imaging that provides scientifically and clinically valuable information about brain tissue microstructure but suffers from poor robustness to noise, especially in voxels containing tightly packed aligned axons.
arxiv  

Diffusion Tensor Imaging in Anxiety Disorders

Current Psychiatry Reports, 2012
Diffusion tensor imaging (DTI) can be used to examine the structural integrity of regional white matter and to map white matter tracts. DTI studies have been performed in several psychiatric disorders, especially in those for which a developmental or a neuropsychiatric component was postulated.
Moji Aghajani, Elliot Ayling, Jean-Paul Fouche, Jean-Paul Fouche, Nic J.A. van der Wee   +4 more
openaire   +8 more sources

Bayesian regularization of diffusion tensor images [PDF]

Biostatistics, 2006
Diffusion tensor imaging (DTI) is a powerful tool in the study of the course of nerve fiber bundles in the human brain. Using DTI, the local fiber orientation in each image voxel can be described by a diffusion tensor which is constructed from local measurements of diffusion coefficients along several directions. The measured diffusion coefficients and
Frandsen, Jesper, Hobolth, Asger, Østergaard, Leif, Vestergaard-Poulsen, Peter, Jensen, Eva Bjørn Vedel   +4 more
openaire   +2 more sources

Brain diffusion tensor imaging in dogs with degenerative myelopathy

Journal of Veterinary Internal Medicine, 2021
Background Degenerative myelopathy (DM) in dogs shares similarities with superoxide dismutase 1‐associated human amyotrophic lateral sclerosis (ALS).
Melissa J. Lewis, Jeremy L. Shomper, Baye G. Williamson, Daniella P. Vansteenkiste, Katherine F. Bibi, Stefanie H. Y. Lim, Joseph B. Kowal, Joan R. Coates   +7 more
doaj   +1 more source

Introduction to Brain and Medical Images [PDF]

arXiv, 2021
This article is based on the first chapter of book Chung (2013), where brain and medical images are introduced. The most widely used brain imaging modalities are magnetic resonance images (MRI), functional-MRI (fMRI) and diffusion tensor images (DTI). A brief introduction to each imaging modality is explained.
arxiv  

Construction of Human Brain Templates with Diffusion Tensor Imaging Data: A Review

Chinese Journal of Magnetic Resonance, 2018
Diffusion-weighted magnetic resonance images contain rich information on brain white matter (WM), and have been used to construct brain templates/atlases.
JIANG Fan, WANG Yuan-jun
doaj   +1 more source

Normal quantitative values of diffusion tensor imaging of the cervical spinal cord with 3.0T MRI in the Mexican population

Journal of the Mexican Federation of Radiology and Imaging, 2023
Introduction: Diffusion tensor imaging measurements have not been standardized nor normal values defined at different cervical spinal cord levels. This study determined the normal quantitative values of diffusion tensor imaging with 3.0T MRI in the ...
Jorge Paz-Gutierrez, Byron A. Portilla-Benavides, William F. Bermudez-Bravo, Victor E. Muñoz-Martinez   +3 more
doaj   +1 more source

MR diffusion tensor spectroscopy and imaging

Biophysical Journal, 1994
This paper describes a new NMR imaging modality--MR diffusion tensor imaging. It consists of estimating an effective diffusion tensor, Deff, within a voxel, and then displaying useful quantities derived from it. We show how the phenomenon of anisotropic diffusion of water (or metabolites) in anisotropic tissues, measured noninvasively by these NMR ...
Basser, P. J., Mattiello, J., Le Bihan, D.   +2 more
openaire   +4 more sources

Generalized diffusion tensor imaging and analytical relationships between diffusion tensor imaging and high angular resolution diffusion imaging [PDF]

Magnetic Resonance in Medicine, 2003
AbstractA new method for mapping diffusivity profiles in tissue is presented. The Bloch‐Torrey equation is modified to include a diffusion term with an arbitrary rank Cartesian tensor. This equation is solved to give the expression for the generalized Stejskal‐Tanner formula quantifying diffusive attenuation in complicated geometries.
Thomas H. Mareci, Evren Özarslan
openaire   +3 more sources

Highlight Specular Reflection Separation based on Tensor Low-rank and Sparse Decomposition Using Polarimetric Cues [PDF]

arXiv, 2022
This paper is concerned with specular reflection removal based on tensor low-rank decomposition framework with the help of polarization information. Our method is motivated by the observation that the specular highlight of an image is sparsely distributed while the remaining diffuse reflection can be well approximated by a linear combination of several
arxiv