A magnetic resonance image based atlas of the rabbit brain for automatic parcellation.

Rabbit brain has been used in several works for the analysis of neurodevelopment. However, there are not specific digital rabbit brain atlases that allow an automatic identification of brain regions, which is a crucial step for various neuroimage analyses, and, instead, manual delineation of areas o...

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Autores principales: Emma Muñoz-Moreno, Ariadna Arbat-Plana, Dafnis Batalle, Guadalupe Soria, Miriam Illa, Alberto Prats-Galino, Elisenda Eixarch, Eduard Gratacos
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Publicado: Public Library of Science (PLoS) 2013
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Acceso en línea:https://doaj.org/article/b278a61de7154aed996a4268bd78614a
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spelling oai:doaj.org-article:b278a61de7154aed996a4268bd78614a2021-11-18T07:39:09ZA magnetic resonance image based atlas of the rabbit brain for automatic parcellation.1932-620310.1371/journal.pone.0067418https://doaj.org/article/b278a61de7154aed996a4268bd78614a2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23844007/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Rabbit brain has been used in several works for the analysis of neurodevelopment. However, there are not specific digital rabbit brain atlases that allow an automatic identification of brain regions, which is a crucial step for various neuroimage analyses, and, instead, manual delineation of areas of interest must be performed in order to evaluate a specific structure. For this reason, we propose an atlas of the rabbit brain based on magnetic resonance imaging, including both structural and diffusion weighted, that can be used for the automatic parcellation of the rabbit brain. Ten individual atlases, as well as an average template and probabilistic maps of the anatomical regions were built. In addition, an example of automatic segmentation based on this atlas is described.Emma Muñoz-MorenoAriadna Arbat-PlanaDafnis BatalleGuadalupe SoriaMiriam IllaAlberto Prats-GalinoElisenda EixarchEduard GratacosPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 7, p e67418 (2013)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Emma Muñoz-Moreno
Ariadna Arbat-Plana
Dafnis Batalle
Guadalupe Soria
Miriam Illa
Alberto Prats-Galino
Elisenda Eixarch
Eduard Gratacos
A magnetic resonance image based atlas of the rabbit brain for automatic parcellation.
description Rabbit brain has been used in several works for the analysis of neurodevelopment. However, there are not specific digital rabbit brain atlases that allow an automatic identification of brain regions, which is a crucial step for various neuroimage analyses, and, instead, manual delineation of areas of interest must be performed in order to evaluate a specific structure. For this reason, we propose an atlas of the rabbit brain based on magnetic resonance imaging, including both structural and diffusion weighted, that can be used for the automatic parcellation of the rabbit brain. Ten individual atlases, as well as an average template and probabilistic maps of the anatomical regions were built. In addition, an example of automatic segmentation based on this atlas is described.
format article
author Emma Muñoz-Moreno
Ariadna Arbat-Plana
Dafnis Batalle
Guadalupe Soria
Miriam Illa
Alberto Prats-Galino
Elisenda Eixarch
Eduard Gratacos
author_facet Emma Muñoz-Moreno
Ariadna Arbat-Plana
Dafnis Batalle
Guadalupe Soria
Miriam Illa
Alberto Prats-Galino
Elisenda Eixarch
Eduard Gratacos
author_sort Emma Muñoz-Moreno
title A magnetic resonance image based atlas of the rabbit brain for automatic parcellation.
title_short A magnetic resonance image based atlas of the rabbit brain for automatic parcellation.
title_full A magnetic resonance image based atlas of the rabbit brain for automatic parcellation.
title_fullStr A magnetic resonance image based atlas of the rabbit brain for automatic parcellation.
title_full_unstemmed A magnetic resonance image based atlas of the rabbit brain for automatic parcellation.
title_sort magnetic resonance image based atlas of the rabbit brain for automatic parcellation.
publisher Public Library of Science (PLoS)
publishDate 2013
url https://doaj.org/article/b278a61de7154aed996a4268bd78614a
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