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Interactive visualization and analysis of morphological skeletons of brain vasculature networks with VessMorphoVis

MOTIVATION: Accurate morphological models of brain vasculature are key to modeling and simulating cerebral blood flow in realistic vascular networks. This in silico approach is fundamental to revealing the principles of neurovascular coupling. Validating those vascular morphologies entails performin...

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Autores principales: Abdellah, Marwan, Guerrero, Nadir Román, Lapere, Samuel, Coggan, Jay S, Keller, Daniel, Coste, Benoit, Dagar, Snigdha, Courcol, Jean-Denis, Markram, Henry, Schürmann, Felix
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355309/
https://www.ncbi.nlm.nih.gov/pubmed/32657395
http://dx.doi.org/10.1093/bioinformatics/btaa461
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author Abdellah, Marwan
Guerrero, Nadir Román
Lapere, Samuel
Coggan, Jay S
Keller, Daniel
Coste, Benoit
Dagar, Snigdha
Courcol, Jean-Denis
Markram, Henry
Schürmann, Felix
author_facet Abdellah, Marwan
Guerrero, Nadir Román
Lapere, Samuel
Coggan, Jay S
Keller, Daniel
Coste, Benoit
Dagar, Snigdha
Courcol, Jean-Denis
Markram, Henry
Schürmann, Felix
author_sort Abdellah, Marwan
collection PubMed
description MOTIVATION: Accurate morphological models of brain vasculature are key to modeling and simulating cerebral blood flow in realistic vascular networks. This in silico approach is fundamental to revealing the principles of neurovascular coupling. Validating those vascular morphologies entails performing certain visual analysis tasks that cannot be accomplished with generic visualization frameworks. This limitation has a substantial impact on the accuracy of the vascular models employed in the simulation. RESULTS: We present VessMorphoVis, an integrated suite of toolboxes for interactive visualization and analysis of vast brain vascular networks represented by morphological graphs segmented originally from imaging or microscopy stacks. Our workflow leverages the outstanding potentials of Blender, aiming to establish an integrated, extensible and domain-specific framework capable of interactive visualization, analysis, repair, high-fidelity meshing and high-quality rendering of vascular morphologies. Based on the initial feedback of the users, we anticipate that our framework will be an essential component in vascular modeling and simulation in the future, filling a gap that is at present largely unfulfilled. AVAILABILITY AND IMPLEMENTATION: VessMorphoVis is freely available under the GNU public license on Github at https://github.com/BlueBrain/VessMorphoVis. The morphology analysis, visualization, meshing and rendering modules are implemented as an add-on for Blender 2.8 based on its Python API (application programming interface). The add-on functionality is made available to users through an intuitive graphical user interface, as well as through exhaustive configuration files calling the API via a feature-rich command line interface running Blender in background mode. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-73553092020-07-16 Interactive visualization and analysis of morphological skeletons of brain vasculature networks with VessMorphoVis Abdellah, Marwan Guerrero, Nadir Román Lapere, Samuel Coggan, Jay S Keller, Daniel Coste, Benoit Dagar, Snigdha Courcol, Jean-Denis Markram, Henry Schürmann, Felix Bioinformatics General Computational Biology MOTIVATION: Accurate morphological models of brain vasculature are key to modeling and simulating cerebral blood flow in realistic vascular networks. This in silico approach is fundamental to revealing the principles of neurovascular coupling. Validating those vascular morphologies entails performing certain visual analysis tasks that cannot be accomplished with generic visualization frameworks. This limitation has a substantial impact on the accuracy of the vascular models employed in the simulation. RESULTS: We present VessMorphoVis, an integrated suite of toolboxes for interactive visualization and analysis of vast brain vascular networks represented by morphological graphs segmented originally from imaging or microscopy stacks. Our workflow leverages the outstanding potentials of Blender, aiming to establish an integrated, extensible and domain-specific framework capable of interactive visualization, analysis, repair, high-fidelity meshing and high-quality rendering of vascular morphologies. Based on the initial feedback of the users, we anticipate that our framework will be an essential component in vascular modeling and simulation in the future, filling a gap that is at present largely unfulfilled. AVAILABILITY AND IMPLEMENTATION: VessMorphoVis is freely available under the GNU public license on Github at https://github.com/BlueBrain/VessMorphoVis. The morphology analysis, visualization, meshing and rendering modules are implemented as an add-on for Blender 2.8 based on its Python API (application programming interface). The add-on functionality is made available to users through an intuitive graphical user interface, as well as through exhaustive configuration files calling the API via a feature-rich command line interface running Blender in background mode. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-07 2020-07-13 /pmc/articles/PMC7355309/ /pubmed/32657395 http://dx.doi.org/10.1093/bioinformatics/btaa461 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle General Computational Biology
Abdellah, Marwan
Guerrero, Nadir Román
Lapere, Samuel
Coggan, Jay S
Keller, Daniel
Coste, Benoit
Dagar, Snigdha
Courcol, Jean-Denis
Markram, Henry
Schürmann, Felix
Interactive visualization and analysis of morphological skeletons of brain vasculature networks with VessMorphoVis
title Interactive visualization and analysis of morphological skeletons of brain vasculature networks with VessMorphoVis
title_full Interactive visualization and analysis of morphological skeletons of brain vasculature networks with VessMorphoVis
title_fullStr Interactive visualization and analysis of morphological skeletons of brain vasculature networks with VessMorphoVis
title_full_unstemmed Interactive visualization and analysis of morphological skeletons of brain vasculature networks with VessMorphoVis
title_short Interactive visualization and analysis of morphological skeletons of brain vasculature networks with VessMorphoVis
title_sort interactive visualization and analysis of morphological skeletons of brain vasculature networks with vessmorphovis
topic General Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355309/
https://www.ncbi.nlm.nih.gov/pubmed/32657395
http://dx.doi.org/10.1093/bioinformatics/btaa461
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