With diffusion tensor MRI one has access to the organization in space
of tissue microstructural components. This outstanding potential
adds, however, another layer of complexity to the diffusion MRI
data acquisition and analysis processes. Over the last few years
many articles have been published dealing with those matters. This
special issue is thus timely to provide readers with the synthesis
and the overall viewpoints from leading contributors to the field.
%0 Journal Article
%1 Bihan2002
%A Bihan, Denis Le
%A van Zijl, Peter
%D 2002
%J NMR Biomed
%K Diffusion, Myelinated, Networks Neural Imaging, Resonance Nerve Water, Magnetic Fibers, Anisotropy, (Computer), Chemistry, 12489093 Brain Diffusion Brain,
%N 7-8
%P 431--434
%R 10.1002/nbm.798
%T From the diffusion coefficient to the diffusion tensor.
%U http://dx.doi.org/10.1002/nbm.798
%V 15
%X With diffusion tensor MRI one has access to the organization in space
of tissue microstructural components. This outstanding potential
adds, however, another layer of complexity to the diffusion MRI
data acquisition and analysis processes. Over the last few years
many articles have been published dealing with those matters. This
special issue is thus timely to provide readers with the synthesis
and the overall viewpoints from leading contributors to the field.
@article{Bihan2002,
abstract = {With diffusion tensor MRI one has access to the organization in space
of tissue microstructural components. This outstanding potential
adds, however, another layer of complexity to the diffusion MRI
data acquisition and analysis processes. Over the last few years
many articles have been published dealing with those matters. This
special issue is thus timely to provide readers with the synthesis
and the overall viewpoints from leading contributors to the field.},
added-at = {2007-01-10T11:32:01.000+0100},
author = {Bihan, Denis Le and van Zijl, Peter},
biburl = {https://www.bibsonomy.org/bibtex/27a95c7bfcc960f4a941a52ce78ca31de/bmeyer},
description = {Diffusion Tensor Imaging (DTI)},
doi = {10.1002/nbm.798},
interhash = {fcaed93748e7c4c49153f686a54c0974},
intrahash = {7a95c7bfcc960f4a941a52ce78ca31de},
journal = {NMR Biomed},
keywords = {Diffusion, Myelinated, Networks Neural Imaging, Resonance Nerve Water, Magnetic Fibers, Anisotropy, (Computer), Chemistry, 12489093 Brain Diffusion Brain,},
number = {7-8},
owner = {bzfbmeye},
pages = {431--434},
pmid = {12489093},
timestamp = {2007-01-10T11:32:01.000+0100},
title = {From the diffusion coefficient to the diffusion tensor.},
url = {http://dx.doi.org/10.1002/nbm.798},
volume = 15,
year = 2002
}