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Extensible visualization and analysis for multidimensional images using Vaa3D

Nature Protocols volume 9, pages 193–208 (2014)Cite this article

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Abstract

Open-Source 3D Visualization-Assisted Analysis (Vaa3D) is a software platform for the visualization and analysis of large-scale multidimensional images. In this protocol we describe how to use several popular features of Vaa3D, including (i) multidimensional image visualization, (ii) 3D image object generation and quantitative measurement, (iii) 3D image comparison, fusion and management, (iv) visualization of heterogeneous images and respective surface objects and (v) extension of Vaa3D functions using its plug-in interface. We also briefly demonstrate how to integrate these functions for complicated applications of microscopic image visualization and quantitative analysis using three exemplar pipelines, including an automated pipeline for image filtering, segmentation and surface generation; an automated pipeline for 3D image stitching; and an automated pipeline for neuron morphology reconstruction, quantification and comparison. Once a user is familiar with Vaa3D, visualization usually runs in real time and analysis takes less than a few minutes for a simple data set.

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Figure 1: Screenshots of visualization of a single 3D fluorescently labeled cellular image stack of the late-embryonic-stage nervous system of Drosophila.
Figure 2: Screenshots showing the creation of 3D markers, 3D line segments and 3D curves for an image and quantitative profiling of image content based on these objects.
Figure 3: Visualization of a 5D image data set of the C. elegans nervous system.
Figure 4: Screenshots showing the creation and visualization of irregular 3D surface meshes for image content of different data channels.
Figure 5: Screenshots of colocalization and fusion of many 3D image stacks.
Figure 6: Screenshots of automated 3D segmentation and quantitative analysis of a 3D cellular image stack.
Figure 7: Pipeline for stitching terabytes of 3D images automatically with the TeraStitcher plug-in.
Figure 8: Screenshots of automated reconstruction and analysis of the 3D morphology of neurons.

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Acknowledgements

We thank Z. Ruan, H. Xiao and Y. Wan for developing several modules briefly discussed in this article; L. Qu, Y. Yu, J. Zhou, L. Ibanez, P. Yu, C. Bruns and many other contributors to the Vaa3D project; C. Doe, E. Heckscher, R. Kerr, J. Simpson, P. Chung, G. Rubin, L. Silvestri, L. Sacconi, F.S. Pavone, http://NeuroMorpho.org/, the Janelia FlyLight project and many other collaborators for providing test data for the demonstrations. We thank the Janelia Farm Research Campus of the Howard Hughes Medical Institute and the Allen Institute for Brain Science for support of this work.

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Authors and Affiliations

  1. Allen Institute for Brain Sciences, Seattle, Washington, USA

    Hanchuan Peng & Zhi Zhou

  2. Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA

    Hanchuan Peng & Fuhui Long

  3. Integrated Research Centre, University Campus Bio-Medico of Rome, Rome, Italy

    Alessandro Bria & Giulio Iannello

  4. Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Cassino, Italy

    Alessandro Bria

  5. BioImage, LLC, Bellevue, Washington, USA

    Fuhui Long

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  1. Hanchuan Peng
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  2. Alessandro Bria
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  3. Zhi Zhou
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  4. Giulio Iannello
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  5. Fuhui Long
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Contributions

H.P. conceived and developed this study; A.B. and G.I. developed the TeraStitcher plug-in; F.L. developed the cell segmentation plug-in; H.P. supervised or assisted all plug-in developments; H.P. wrote the manuscript with the contributions from co-authors. Z.Z. helped in testing the options and in editing the manuscript.

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Correspondence to Hanchuan Peng.

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The authors declare no competing financial interests.

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Peng, H., Bria, A., Zhou, Z. et al. Extensible visualization and analysis for multidimensional images using Vaa3D. Nat Protoc 9, 193–208 (2014). https://doi.org/10.1038/nprot.2014.011

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