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BrainBrowser: distributed, web-based neurological data visualization

Recent years have seen massive, distributed datasets become the norm in neuroimaging research, and the methodologies used to analyze them have, in response, become more collaborative and exploratory. Tools and infrastructure are continuously being developed and deployed to facilitate research in thi...

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Autores principales: Sherif, Tarek, Kassis, Nicolas, Rousseau, Marc-Étienne, Adalat, Reza, Evans, Alan C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4292582/
https://www.ncbi.nlm.nih.gov/pubmed/25628562
http://dx.doi.org/10.3389/fninf.2014.00089
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author Sherif, Tarek
Kassis, Nicolas
Rousseau, Marc-Étienne
Adalat, Reza
Evans, Alan C.
author_facet Sherif, Tarek
Kassis, Nicolas
Rousseau, Marc-Étienne
Adalat, Reza
Evans, Alan C.
author_sort Sherif, Tarek
collection PubMed
description Recent years have seen massive, distributed datasets become the norm in neuroimaging research, and the methodologies used to analyze them have, in response, become more collaborative and exploratory. Tools and infrastructure are continuously being developed and deployed to facilitate research in this context: grid computation platforms to process the data, distributed data stores to house and share them, high-speed networks to move them around and collaborative, often web-based, platforms to provide access to and sometimes manage the entire system. BrainBrowser is a lightweight, high-performance JavaScript visualization library built to provide easy-to-use, powerful, on-demand visualization of remote datasets in this new research environment. BrainBrowser leverages modern web technologies, such as WebGL, HTML5 and Web Workers, to visualize 3D surface and volumetric neuroimaging data in any modern web browser without requiring any browser plugins. It is thus trivial to integrate BrainBrowser into any web-based platform. BrainBrowser is simple enough to produce a basic web-based visualization in a few lines of code, while at the same time being robust enough to create full-featured visualization applications. BrainBrowser can dynamically load the data required for a given visualization, so no network bandwidth needs to be waisted on data that will not be used. BrainBrowser's integration into the standardized web platform also allows users to consider using 3D data visualization in novel ways, such as for data distribution, data sharing and dynamic online publications. BrainBrowser is already being used in two major online platforms, CBRAIN and LORIS, and has been used to make the 1TB MACACC dataset openly accessible.
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spelling pubmed-42925822015-01-27 BrainBrowser: distributed, web-based neurological data visualization Sherif, Tarek Kassis, Nicolas Rousseau, Marc-Étienne Adalat, Reza Evans, Alan C. Front Neuroinform Neuroscience Recent years have seen massive, distributed datasets become the norm in neuroimaging research, and the methodologies used to analyze them have, in response, become more collaborative and exploratory. Tools and infrastructure are continuously being developed and deployed to facilitate research in this context: grid computation platforms to process the data, distributed data stores to house and share them, high-speed networks to move them around and collaborative, often web-based, platforms to provide access to and sometimes manage the entire system. BrainBrowser is a lightweight, high-performance JavaScript visualization library built to provide easy-to-use, powerful, on-demand visualization of remote datasets in this new research environment. BrainBrowser leverages modern web technologies, such as WebGL, HTML5 and Web Workers, to visualize 3D surface and volumetric neuroimaging data in any modern web browser without requiring any browser plugins. It is thus trivial to integrate BrainBrowser into any web-based platform. BrainBrowser is simple enough to produce a basic web-based visualization in a few lines of code, while at the same time being robust enough to create full-featured visualization applications. BrainBrowser can dynamically load the data required for a given visualization, so no network bandwidth needs to be waisted on data that will not be used. BrainBrowser's integration into the standardized web platform also allows users to consider using 3D data visualization in novel ways, such as for data distribution, data sharing and dynamic online publications. BrainBrowser is already being used in two major online platforms, CBRAIN and LORIS, and has been used to make the 1TB MACACC dataset openly accessible. Frontiers Media S.A. 2015-01-13 /pmc/articles/PMC4292582/ /pubmed/25628562 http://dx.doi.org/10.3389/fninf.2014.00089 Text en Copyright © 2015 Sherif, Kassis, Rousseau, Adalat and Evans. 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
Sherif, Tarek
Kassis, Nicolas
Rousseau, Marc-Étienne
Adalat, Reza
Evans, Alan C.
BrainBrowser: distributed, web-based neurological data visualization
title BrainBrowser: distributed, web-based neurological data visualization
title_full BrainBrowser: distributed, web-based neurological data visualization
title_fullStr BrainBrowser: distributed, web-based neurological data visualization
title_full_unstemmed BrainBrowser: distributed, web-based neurological data visualization
title_short BrainBrowser: distributed, web-based neurological data visualization
title_sort brainbrowser: distributed, web-based neurological data visualization
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4292582/
https://www.ncbi.nlm.nih.gov/pubmed/25628562
http://dx.doi.org/10.3389/fninf.2014.00089
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