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ATPP: A Pipeline for Automatic Tractography-Based Brain Parcellation

There is a longstanding effort to parcellate brain into areas based on micro-structural, macro-structural, or connectional features, forming various brain atlases. Among them, connectivity-based parcellation gains much emphasis, especially with the considerable progress of multimodal magnetic resona...

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Detalles Bibliográficos
Autores principales: Li, Hai, Fan, Lingzhong, Zhuo, Junjie, Wang, Jiaojian, Zhang, Yu, Yang, Zhengyi, Jiang, Tianzi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5447055/
https://www.ncbi.nlm.nih.gov/pubmed/28611620
http://dx.doi.org/10.3389/fninf.2017.00035
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author Li, Hai
Fan, Lingzhong
Zhuo, Junjie
Wang, Jiaojian
Zhang, Yu
Yang, Zhengyi
Jiang, Tianzi
author_facet Li, Hai
Fan, Lingzhong
Zhuo, Junjie
Wang, Jiaojian
Zhang, Yu
Yang, Zhengyi
Jiang, Tianzi
author_sort Li, Hai
collection PubMed
description There is a longstanding effort to parcellate brain into areas based on micro-structural, macro-structural, or connectional features, forming various brain atlases. Among them, connectivity-based parcellation gains much emphasis, especially with the considerable progress of multimodal magnetic resonance imaging in the past two decades. The Brainnetome Atlas published recently is such an atlas that follows the framework of connectivity-based parcellation. However, in the construction of the atlas, the deluge of high resolution multimodal MRI data and time-consuming computation poses challenges and there is still short of publically available tools dedicated to parcellation. In this paper, we present an integrated open source pipeline (https://www.nitrc.org/projects/atpp), named Automatic Tractography-based Parcellation Pipeline (ATPP) to realize the framework of parcellation with automatic processing and massive parallel computing. ATPP is developed to have a powerful and flexible command line version, taking multiple regions of interest as input, as well as a user-friendly graphical user interface version for parcellating single region of interest. We demonstrate the two versions by parcellating two brain regions, left precentral gyrus and middle frontal gyrus, on two independent datasets. In addition, ATPP has been successfully utilized and fully validated in a variety of brain regions and the human Brainnetome Atlas, showing the capacity to greatly facilitate brain parcellation.
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spelling pubmed-54470552017-06-13 ATPP: A Pipeline for Automatic Tractography-Based Brain Parcellation Li, Hai Fan, Lingzhong Zhuo, Junjie Wang, Jiaojian Zhang, Yu Yang, Zhengyi Jiang, Tianzi Front Neuroinform Neuroscience There is a longstanding effort to parcellate brain into areas based on micro-structural, macro-structural, or connectional features, forming various brain atlases. Among them, connectivity-based parcellation gains much emphasis, especially with the considerable progress of multimodal magnetic resonance imaging in the past two decades. The Brainnetome Atlas published recently is such an atlas that follows the framework of connectivity-based parcellation. However, in the construction of the atlas, the deluge of high resolution multimodal MRI data and time-consuming computation poses challenges and there is still short of publically available tools dedicated to parcellation. In this paper, we present an integrated open source pipeline (https://www.nitrc.org/projects/atpp), named Automatic Tractography-based Parcellation Pipeline (ATPP) to realize the framework of parcellation with automatic processing and massive parallel computing. ATPP is developed to have a powerful and flexible command line version, taking multiple regions of interest as input, as well as a user-friendly graphical user interface version for parcellating single region of interest. We demonstrate the two versions by parcellating two brain regions, left precentral gyrus and middle frontal gyrus, on two independent datasets. In addition, ATPP has been successfully utilized and fully validated in a variety of brain regions and the human Brainnetome Atlas, showing the capacity to greatly facilitate brain parcellation. Frontiers Media S.A. 2017-05-29 /pmc/articles/PMC5447055/ /pubmed/28611620 http://dx.doi.org/10.3389/fninf.2017.00035 Text en Copyright © 2017 Li, Fan, Zhuo, Wang, Zhang, Yang and Jiang. 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.
spellingShingle Neuroscience
Li, Hai
Fan, Lingzhong
Zhuo, Junjie
Wang, Jiaojian
Zhang, Yu
Yang, Zhengyi
Jiang, Tianzi
ATPP: A Pipeline for Automatic Tractography-Based Brain Parcellation
title ATPP: A Pipeline for Automatic Tractography-Based Brain Parcellation
title_full ATPP: A Pipeline for Automatic Tractography-Based Brain Parcellation
title_fullStr ATPP: A Pipeline for Automatic Tractography-Based Brain Parcellation
title_full_unstemmed ATPP: A Pipeline for Automatic Tractography-Based Brain Parcellation
title_short ATPP: A Pipeline for Automatic Tractography-Based Brain Parcellation
title_sort atpp: a pipeline for automatic tractography-based brain parcellation
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5447055/
https://www.ncbi.nlm.nih.gov/pubmed/28611620
http://dx.doi.org/10.3389/fninf.2017.00035
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