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BigDataViewer: visualization and processing for large image data sets

Nature Methods volume 12, pages 481–483 (2015)Cite this article

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To the Editor:

The increasingly popular light-sheet microscopy techniques generate very large three-dimensional (3D) time-lapse recordings of living biological specimens1. The need to make large volumetric data sets available for interactive visualization and analysis has been widely recognized2. However, existing solutions build upon proprietary file formats requiring that data are copy converted before visualization, or they use dedicated servers to generate virtual slices that are transferred to client applications. In practice, the latter leads to frame rates (under ten frames per second) that are insufficient for a truly interactive experience. An easily accessible and extensible open-source solution for interactive arbitrary virtual reslicing of very large volumes and time series of volumes has been missing (Supplementary Note 1).

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Figure 1: Overview of the BDV rendering principle and functionality.

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Acknowledgements

We thank F. Jug for proofreading and helpful discussions; H. Moon (Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG) Scientific Computing Facility) for help with server development and stress-testing; E. Stamataki, A. Cardona and R. Fetter for data sets used in supplementary movies; and J. Schindelin and C. Rueden for developing and maintaining the Fiji infrastructure. S.P. was supported by MPI-CBG, Howard Hughes Medical Institute (HHMI) and the Human Frontier Science Program (HFSP) long-term fellowship LT000783/2012. S.S. was supported by HHMI and MPI-CBG. P.T. and T.P. were supported by The European Research Council Community's Seventh Framework Program (FP7/2007-2013), grant agreement 260746.

Author information

Authors and Affiliations

  1. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany

    Tobias Pietzsch, Stephan Preibisch & Pavel Tomancak

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

    Stephan Saalfeld & Stephan Preibisch

  3. Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, New York, USA

    Stephan Preibisch

  4. Gruss Lipper Biophotonics Center, Albert Einstein College of Medicine, Bronx, USA, New York

    Stephan Preibisch

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  1. Tobias Pietzsch
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  2. Stephan Saalfeld
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  4. Pavel Tomancak
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Corresponding authors

Correspondence to Tobias Pietzsch or Pavel Tomancak.

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Supplementary information

Supplementary Text and Figures

Supplementary Notes 1–6 (PDF 4138 kb)

Supplementary Video 1

Annotated screencast of BigDataViewer functionality Basic BigDataViewer functionality, demonstrated on a large local XML/HDF5 dataset. The dataset is a 500GB SPIM time-lapse of Drosophila melanogaster embryo expressing Histone-YFP in all cells, comprising 250 timepoints with 6 angles each. The data was acquired on a Zeiss Lightsheet Z.1 microscope. (MP4 41966 kb)

Supplementary Video 2

Annotated screencast of BigDataViewer integration with SPIM image processing pipeline Visualizing one time-point of a multi-angle SPIM recording of Drosophila embryo expressing Histone-YFP in all cells, before registration, after registration, and after deconvolution with Fiji's SPIM image processing tools. (MP4 18154 kb)

Supplementary Video 3

Screencast of BigDataViewer navigation through online CATMAID image dataset BigDataViewer mediated navigation through electron microscopy dataset presented through a CATMAID data backend. The registered serial section Transmission Electron Microscopy (TEM) series contains 1.5 segments of the ventral nerve cord of a first-instar Drosophila larva (458 sections, each section consisting of ~ 70 overlapping image tiles, imaged at 4nm/px with 50nm section thickness). This dataset was collected by Albert Cardona, Wayne Pereanu and Rick Fetter at Janelia Research Campus and was first introduced in this publication dealing with serial section TEM elastic reconstruction: Saalfeld S., Fetter R., Cardona A., Tomancak P. (2012) Elastic Volume Reconstruction from Series of Ultra-thin Microscopy Sections Nature Methods 9(7), 717-720 (MP4 22541 kb)

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Pietzsch, T., Saalfeld, S., Preibisch, S. et al. BigDataViewer: visualization and processing for large image data sets. Nat Methods 12, 481–483 (2015). https://doi.org/10.1038/nmeth.3392

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