Estimating Fiber Orientation Distribution Functions in 3D-Polarized Light Imaging

Research of the human brain connectome requires multiscale approaches derived from independent imaging methods ideally applied to the same object. Hence, comprehensible strategies for data integration across modalities and across scales are essential. We have successfully established a concept to br...

Full description

Bibliographic Details
Main Authors:	Axer, Markus, Strohmer, Sven, Gräßel, David, Bücker, Oliver, Dohmen, Melanie, Reckfort, Julia, Zilles, Karl, Amunts, Katrin
Format:	Online
Language:	English
Published:	Frontiers Media S.A. 2016
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4835454/

id	pubmed-4835454
recordtype	oai_dc
spelling	pubmed-48354542016-05-04 Estimating Fiber Orientation Distribution Functions in 3D-Polarized Light Imaging Axer, Markus Strohmer, Sven Gräßel, David Bücker, Oliver Dohmen, Melanie Reckfort, Julia Zilles, Karl Amunts, Katrin Neuroscience Research of the human brain connectome requires multiscale approaches derived from independent imaging methods ideally applied to the same object. Hence, comprehensible strategies for data integration across modalities and across scales are essential. We have successfully established a concept to bridge the spatial scales from microscopic fiber orientation measurements based on 3D-Polarized Light Imaging (3D-PLI) to meso- or macroscopic dimensions. By creating orientation distribution functions (pliODFs) from high-resolution vector data via series expansion with spherical harmonics utilizing high performance computing and supercomputing technologies, data fusion with Diffusion Magnetic Resonance Imaging has become feasible, even for a large-scale dataset such as the human brain. Validation of our approach was done effectively by means of two types of datasets that were transferred from fiber orientation maps into pliODFs: simulated 3D-PLI data showing artificial, but clearly defined fiber patterns and real 3D-PLI data derived from sections through the human brain and the brain of a hooded seal. Frontiers Media S.A. 2016-04-19 /pmc/articles/PMC4835454/ /pubmed/27147981 http://dx.doi.org/10.3389/fnana.2016.00040 Text en Copyright © 2016 Axer, Strohmer, Gräßel, Bücker, Dohmen, Reckfort, Zilles and Amunts. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Axer, Markus Strohmer, Sven Gräßel, David Bücker, Oliver Dohmen, Melanie Reckfort, Julia Zilles, Karl Amunts, Katrin
spellingShingle	Axer, Markus Strohmer, Sven Gräßel, David Bücker, Oliver Dohmen, Melanie Reckfort, Julia Zilles, Karl Amunts, Katrin Estimating Fiber Orientation Distribution Functions in 3D-Polarized Light Imaging
author_facet	Axer, Markus Strohmer, Sven Gräßel, David Bücker, Oliver Dohmen, Melanie Reckfort, Julia Zilles, Karl Amunts, Katrin
author_sort	Axer, Markus
title	Estimating Fiber Orientation Distribution Functions in 3D-Polarized Light Imaging
title_short	Estimating Fiber Orientation Distribution Functions in 3D-Polarized Light Imaging
title_full	Estimating Fiber Orientation Distribution Functions in 3D-Polarized Light Imaging
title_fullStr	Estimating Fiber Orientation Distribution Functions in 3D-Polarized Light Imaging
title_full_unstemmed	Estimating Fiber Orientation Distribution Functions in 3D-Polarized Light Imaging
title_sort	estimating fiber orientation distribution functions in 3d-polarized light imaging
description	Research of the human brain connectome requires multiscale approaches derived from independent imaging methods ideally applied to the same object. Hence, comprehensible strategies for data integration across modalities and across scales are essential. We have successfully established a concept to bridge the spatial scales from microscopic fiber orientation measurements based on 3D-Polarized Light Imaging (3D-PLI) to meso- or macroscopic dimensions. By creating orientation distribution functions (pliODFs) from high-resolution vector data via series expansion with spherical harmonics utilizing high performance computing and supercomputing technologies, data fusion with Diffusion Magnetic Resonance Imaging has become feasible, even for a large-scale dataset such as the human brain. Validation of our approach was done effectively by means of two types of datasets that were transferred from fiber orientation maps into pliODFs: simulated 3D-PLI data showing artificial, but clearly defined fiber patterns and real 3D-PLI data derived from sections through the human brain and the brain of a hooded seal.
publisher	Frontiers Media S.A.
publishDate	2016
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4835454/
_version_	1613567579255734272

Estimating Fiber Orientation Distribution Functions in 3D-Polarized Light Imaging

Similar Items