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Object-based representation and analysis of light and electron microscopic volume data using Blender

BACKGROUND: Rapid improvements in light and electron microscopy imaging techniques and the development of 3D anatomical atlases necessitate new approaches for the visualization and analysis of image data. Pixel-based representations of raw light microscopy data suffer from limitations in the number...

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Autores principales: Asadulina, Albina, Conzelmann, Markus, Williams, Elizabeth A., Panzera, Aurora, Jékely, Gáspár
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4513682/
https://www.ncbi.nlm.nih.gov/pubmed/26208945
http://dx.doi.org/10.1186/s12859-015-0652-7
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author Asadulina, Albina
Conzelmann, Markus
Williams, Elizabeth A.
Panzera, Aurora
Jékely, Gáspár
author_facet Asadulina, Albina
Conzelmann, Markus
Williams, Elizabeth A.
Panzera, Aurora
Jékely, Gáspár
author_sort Asadulina, Albina
collection PubMed
description BACKGROUND: Rapid improvements in light and electron microscopy imaging techniques and the development of 3D anatomical atlases necessitate new approaches for the visualization and analysis of image data. Pixel-based representations of raw light microscopy data suffer from limitations in the number of channels that can be visualized simultaneously. Complex electron microscopic reconstructions from large tissue volumes are also challenging to visualize and analyze. RESULTS: Here we exploit the advanced visualization capabilities and flexibility of the open-source platform Blender to visualize and analyze anatomical atlases. We use light-microscopy-based gene expression atlases and electron microscopy connectome volume data from larval stages of the marine annelid Platynereis dumerilii. We build object-based larval gene expression atlases in Blender and develop tools for annotation and coexpression analysis. We also represent and analyze connectome data including neuronal reconstructions and underlying synaptic connectivity. CONCLUSIONS: We demonstrate the power and flexibility of Blender for visualizing and exploring complex anatomical atlases. The resources we have developed for Platynereis will facilitate data sharing and the standardization of anatomical atlases for this species. The flexibility of Blender, particularly its embedded Python application programming interface, means that our methods can be easily extended to other organisms. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0652-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-45136822015-07-25 Object-based representation and analysis of light and electron microscopic volume data using Blender Asadulina, Albina Conzelmann, Markus Williams, Elizabeth A. Panzera, Aurora Jékely, Gáspár BMC Bioinformatics Research Article BACKGROUND: Rapid improvements in light and electron microscopy imaging techniques and the development of 3D anatomical atlases necessitate new approaches for the visualization and analysis of image data. Pixel-based representations of raw light microscopy data suffer from limitations in the number of channels that can be visualized simultaneously. Complex electron microscopic reconstructions from large tissue volumes are also challenging to visualize and analyze. RESULTS: Here we exploit the advanced visualization capabilities and flexibility of the open-source platform Blender to visualize and analyze anatomical atlases. We use light-microscopy-based gene expression atlases and electron microscopy connectome volume data from larval stages of the marine annelid Platynereis dumerilii. We build object-based larval gene expression atlases in Blender and develop tools for annotation and coexpression analysis. We also represent and analyze connectome data including neuronal reconstructions and underlying synaptic connectivity. CONCLUSIONS: We demonstrate the power and flexibility of Blender for visualizing and exploring complex anatomical atlases. The resources we have developed for Platynereis will facilitate data sharing and the standardization of anatomical atlases for this species. The flexibility of Blender, particularly its embedded Python application programming interface, means that our methods can be easily extended to other organisms. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0652-7) contains supplementary material, which is available to authorized users. BioMed Central 2015-07-25 /pmc/articles/PMC4513682/ /pubmed/26208945 http://dx.doi.org/10.1186/s12859-015-0652-7 Text en © Asadulina et al. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Asadulina, Albina
Conzelmann, Markus
Williams, Elizabeth A.
Panzera, Aurora
Jékely, Gáspár
Object-based representation and analysis of light and electron microscopic volume data using Blender
title Object-based representation and analysis of light and electron microscopic volume data using Blender
title_full Object-based representation and analysis of light and electron microscopic volume data using Blender
title_fullStr Object-based representation and analysis of light and electron microscopic volume data using Blender
title_full_unstemmed Object-based representation and analysis of light and electron microscopic volume data using Blender
title_short Object-based representation and analysis of light and electron microscopic volume data using Blender
title_sort object-based representation and analysis of light and electron microscopic volume data using blender
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4513682/
https://www.ncbi.nlm.nih.gov/pubmed/26208945
http://dx.doi.org/10.1186/s12859-015-0652-7
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