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NeuroMorphoVis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks

MOTIVATION: From image stacks to computational models, processing digital representations of neuronal morphologies is essential to neuroscientific research. Workflows involve various techniques and tools, leading in certain cases to convoluted and fragmented pipelines. The existence of an integrated...

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Detalles Bibliográficos
Autores principales: Abdellah, Marwan, Hernando, Juan, Eilemann, Stefan, Lapere, Samuel, Antille, Nicolas, Markram, Henry, Schürmann, Felix
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022592/
https://www.ncbi.nlm.nih.gov/pubmed/29949998
http://dx.doi.org/10.1093/bioinformatics/bty231
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author Abdellah, Marwan
Hernando, Juan
Eilemann, Stefan
Lapere, Samuel
Antille, Nicolas
Markram, Henry
Schürmann, Felix
author_facet Abdellah, Marwan
Hernando, Juan
Eilemann, Stefan
Lapere, Samuel
Antille, Nicolas
Markram, Henry
Schürmann, Felix
author_sort Abdellah, Marwan
collection PubMed
description MOTIVATION: From image stacks to computational models, processing digital representations of neuronal morphologies is essential to neuroscientific research. Workflows involve various techniques and tools, leading in certain cases to convoluted and fragmented pipelines. The existence of an integrated, extensible and free framework for processing, analysis and visualization of those morphologies is a challenge that is still largely unfulfilled. RESULTS: We present NeuroMorphoVis, an interactive, extensible and cross-platform framework for building, visualizing and analyzing digital reconstructions of neuronal morphology skeletons extracted from microscopy stacks. Our framework is capable of detecting and repairing tracing artifacts, allowing the generation of high fidelity surface meshes and high resolution volumetric models for simulation and in silico imaging studies. The applicability of NeuroMorphoVis is demonstrated with two case studies. The first simulates the construction of three-dimensional profiles of neuronal somata and the other highlights how the framework is leveraged to create volumetric models of neuronal circuits for simulating different types of in vitro imaging experiments. AVAILABILITY AND IMPLEMENTATION: The source code and documentation are freely available on https://github.com/BlueBrain/NeuroMorphoVis under the GNU public license. The morphological analysis, visualization and surface meshing are implemented as an extensible Python API (Application Programming Interface) based on Blender, and the volume reconstruction and analysis code is written in C++ and parallelized using OpenMP. The framework features are accessible from a user-friendly GUI (Graphical User Interface) and a rich CLI (Command Line Interface). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-60225922018-07-10 NeuroMorphoVis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks Abdellah, Marwan Hernando, Juan Eilemann, Stefan Lapere, Samuel Antille, Nicolas Markram, Henry Schürmann, Felix Bioinformatics Ismb 2018–Intelligent Systems for Molecular Biology Proceedings MOTIVATION: From image stacks to computational models, processing digital representations of neuronal morphologies is essential to neuroscientific research. Workflows involve various techniques and tools, leading in certain cases to convoluted and fragmented pipelines. The existence of an integrated, extensible and free framework for processing, analysis and visualization of those morphologies is a challenge that is still largely unfulfilled. RESULTS: We present NeuroMorphoVis, an interactive, extensible and cross-platform framework for building, visualizing and analyzing digital reconstructions of neuronal morphology skeletons extracted from microscopy stacks. Our framework is capable of detecting and repairing tracing artifacts, allowing the generation of high fidelity surface meshes and high resolution volumetric models for simulation and in silico imaging studies. The applicability of NeuroMorphoVis is demonstrated with two case studies. The first simulates the construction of three-dimensional profiles of neuronal somata and the other highlights how the framework is leveraged to create volumetric models of neuronal circuits for simulating different types of in vitro imaging experiments. AVAILABILITY AND IMPLEMENTATION: The source code and documentation are freely available on https://github.com/BlueBrain/NeuroMorphoVis under the GNU public license. The morphological analysis, visualization and surface meshing are implemented as an extensible Python API (Application Programming Interface) based on Blender, and the volume reconstruction and analysis code is written in C++ and parallelized using OpenMP. The framework features are accessible from a user-friendly GUI (Graphical User Interface) and a rich CLI (Command Line Interface). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2018-07-01 2018-06-27 /pmc/articles/PMC6022592/ /pubmed/29949998 http://dx.doi.org/10.1093/bioinformatics/bty231 Text en © The Author(s) 2018. 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 Ismb 2018–Intelligent Systems for Molecular Biology Proceedings
Abdellah, Marwan
Hernando, Juan
Eilemann, Stefan
Lapere, Samuel
Antille, Nicolas
Markram, Henry
Schürmann, Felix
NeuroMorphoVis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks
title NeuroMorphoVis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks
title_full NeuroMorphoVis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks
title_fullStr NeuroMorphoVis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks
title_full_unstemmed NeuroMorphoVis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks
title_short NeuroMorphoVis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks
title_sort neuromorphovis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks
topic Ismb 2018–Intelligent Systems for Molecular Biology Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022592/
https://www.ncbi.nlm.nih.gov/pubmed/29949998
http://dx.doi.org/10.1093/bioinformatics/bty231
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