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Biological imaging software tools

Nature Methods volume 9, pages 697–710 (2012)Cite this article

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A Corrigendum to this article was published on 27 September 2012

A Corrigendum to this article was published on 27 September 2012

This article has been updated

Abstract

Few technologies are more widespread in modern biological laboratories than imaging. Recent advances in optical technologies and instrumentation are providing hitherto unimagined capabilities. Almost all these advances have required the development of software to enable the acquisition, management, analysis and visualization of the imaging data. We review each computational step that biologists encounter when dealing with digital images, the inherent challenges and the overall status of available software for bioimage informatics, focusing on open-source options.

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Figure 1: Overview of imaging workflow.
Figure 2
Figure 3
Figure 4
Figure 5: Screenshots illustrating the image-analysis steps starting from a multichannel, multiphoton time-lapse movie culminating in a bioinformatics profiling of the extracted spatiotemporal data, using the FARSIGHT toolkit.
Figure 6
Figure 7: Machine learning.
Figure 8: Workflow systems.

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  • 20 July 2012

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  • 29 August 2012

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Acknowledgements

We acknowledge our respective funding sources and members of our laboratories for feedback and useful comments, in particular A. Merouane and A. Narayanswamy of the Roysam lab for their assistance in preparing figures, and L. Kamentsky and M. Bray of the Carpenter lab for useful input and edits on the manuscript. A.E.C. and K.W.E. were supported by US National Institutes of Health grants R01 GM089652 (to A.E.C.) and RC2 GM092519 (to K.W.E.).

Author information

Authors and Affiliations

  1. Laboratory for Optical and Computational Instrumentation, University of Wisconsin at Madison, Madison, Wisconsin, USA

    Kevin W Eliceiri

  2. Department of Computer and Information Science, Universität Konstanz, Konstanz, Germany

    Michael R Berthold

  3. National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA

    Ilya G Goldberg

  4. Kitware Inc., New York, New York, USA

    Luis Ibáñez

  5. Department of Electrical and Computer Engineering, Center for Bio-image Informatics, University of California Santa Barbara, Santa Barbara, California, USA

    B S Manjunath

  6. National Center for Microscopy and Imaging Research, University of California San Diego, La Jolla, California, USA

    Maryann E Martone

  7. Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

    Robert F Murphy

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

    Hanchuan Peng

  9. Biochemical Science Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA

    Anne L Plant

  10. Department of Electrical and Computer Engineering, University of Houston, Houston, Texas, USA

    Badrinath Roysam

  11. Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, California, USA

    Nico Stuurman

  12. Wellcome Trust Centre for Gene Regulation and Expression, University of Dundee, Dundee, UK

    Jason R Swedlow

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

    Pavel Tomancak

  14. Imaging Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Anne E Carpenter

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Corresponding authors

Correspondence to Kevin W Eliceiri or Anne E Carpenter.

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Competing interests

J.R.S. is affiliated with Glencoe Software, Inc., a company that contributes to OMERO. M.R.B. is co-founder and co-owner of KNIME.com AG, a company that contributes to the development of the KNIME platform.

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Eliceiri, K., Berthold, M., Goldberg, I. et al. Biological imaging software tools. Nat Methods 9, 697–710 (2012). https://doi.org/10.1038/nmeth.2084

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