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

Asadulina A, Conzelmann M, Williams EA, Panzera A, Jékely G - BMC Bioinformatics (2015)

Bottom Line: Complex electron microscopic reconstructions from large tissue volumes are also challenging to visualize and analyze.We also represent and analyze connectome data including neuronal reconstructions and underlying synaptic connectivity.The flexibility of Blender, particularly its embedded Python application programming interface, means that our methods can be easily extended to other organisms.

View Article: PubMed Central - PubMed

Affiliation: Max Planck Institute for Developmental Biology, Spemannstrasse 35, 72076, Tübingen, Germany. albina.asadulina@tuebingen.mpg.de.

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus

Measuring network centrality in Blender for the Platynereis visual neuronal network (a). Degree (b, e), eigenvector (c, f) and closeness centrality (d, g) projected onto the 3D model of the neuronal network
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Fig5: Measuring network centrality in Blender for the Platynereis visual neuronal network (a). Degree (b, e), eigenvector (c, f) and closeness centrality (d, g) projected onto the 3D model of the neuronal network

Mentions: Blender also enables the calculation of statistical parameters and their visualization in a 3D model of a neuronal network. We calculated network centrality measures for the Platynereis eye connectome including degree, eigenvector and closeness centrality, and mapped these measures onto the 3D neuronal model (Fig. 5, Additional files 1 and 2). These centrality measures reflect various aspects of connectivity of the nodes of a network and can therefore represent information flow or highlight the importance of individual neurons in the network (Fig. 5).Fig. 5


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

Asadulina A, Conzelmann M, Williams EA, Panzera A, Jékely G - BMC Bioinformatics (2015)

Measuring network centrality in Blender for the Platynereis visual neuronal network (a). Degree (b, e), eigenvector (c, f) and closeness centrality (d, g) projected onto the 3D model of the neuronal network
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4513682&req=5

Fig5: Measuring network centrality in Blender for the Platynereis visual neuronal network (a). Degree (b, e), eigenvector (c, f) and closeness centrality (d, g) projected onto the 3D model of the neuronal network
Mentions: Blender also enables the calculation of statistical parameters and their visualization in a 3D model of a neuronal network. We calculated network centrality measures for the Platynereis eye connectome including degree, eigenvector and closeness centrality, and mapped these measures onto the 3D neuronal model (Fig. 5, Additional files 1 and 2). These centrality measures reflect various aspects of connectivity of the nodes of a network and can therefore represent information flow or highlight the importance of individual neurons in the network (Fig. 5).Fig. 5

Bottom Line: Complex electron microscopic reconstructions from large tissue volumes are also challenging to visualize and analyze.We also represent and analyze connectome data including neuronal reconstructions and underlying synaptic connectivity.The flexibility of Blender, particularly its embedded Python application programming interface, means that our methods can be easily extended to other organisms.

View Article: PubMed Central - PubMed

Affiliation: Max Planck Institute for Developmental Biology, Spemannstrasse 35, 72076, Tübingen, Germany. albina.asadulina@tuebingen.mpg.de.

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus