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...

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Published in:Frontiers in Neuroanatomy
Main Authors: Axer, Markus, Strohmer, Sven, Gräßel, David, Bücker, Oliver, Dohmen, Melanie, Reckfort, Julia, Zilles, Karl, Amunts, Katrin
Format: Text
Language:English
Published: Frontiers Media S.A. 2016
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Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4835454/
https://doi.org/10.3389/fnana.2016.00040
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spelling ftpubmed:oai:pubmedcentral.nih.gov:4835454 2023-05-15T16:34:49+02:00 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 2016-04-19 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4835454/ https://doi.org/10.3389/fnana.2016.00040 en eng Frontiers Media S.A. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4835454/ http://dx.doi.org/10.3389/fnana.2016.00040 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. CC-BY Neuroscience Text 2016 ftpubmed https://doi.org/10.3389/fnana.2016.00040 2016-05-08T00:19:33Z 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. Text hooded seal PubMed Central (PMC) Frontiers in Neuroanatomy 10
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Neuroscience
spellingShingle Neuroscience
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
topic_facet Neuroscience
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.
format Text
author Axer, Markus
Strohmer, Sven
Gräßel, David
Bücker, Oliver
Dohmen, Melanie
Reckfort, Julia
Zilles, Karl
Amunts, Katrin
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
publisher Frontiers Media S.A.
publishDate 2016
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4835454/
https://doi.org/10.3389/fnana.2016.00040
genre hooded seal
genre_facet hooded seal
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4835454/
http://dx.doi.org/10.3389/fnana.2016.00040
op_rights 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.
op_rightsnorm CC-BY
op_doi https://doi.org/10.3389/fnana.2016.00040
container_title Frontiers in Neuroanatomy
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