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Visualization of image data from cells to organisms

A Corrigendum to this article was published on 01 June 2010

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Abstract

Advances in imaging techniques and high-throughput technologies are providing scientists with unprecedented possibilities to visualize internal structures of cells, organs and organisms and to collect systematic image data characterizing genes and proteins on a large scale. To make the best use of these increasingly complex and large image data resources, the scientific community must be provided with methods to query, analyze and crosslink these resources to give an intuitive visual representation of the data. This review gives an overview of existing methods and tools for this purpose and highlights some of their limitations and challenges.

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Figure 1: Imaging techniques.
Figure 2: Visualization of high–dimensional image data.
Figure 3: Visualization of anatomical features in MRI.
Figure 4: Visualization of high–throughput data.

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Change history

  • 30 April 2010

    In the version of this article initially published, Carl Zeiss Microimaging was not acknowledged for providing access to the SPIM prototype used to generate images in the article. The error has been corrected in the HTML and PDF versions of the article.

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Acknowledgements

P.T. thanks Carl Zeiss Microimaging for SPIM prototype access. T.W. was supported by a grant to J.E. (within the Mitocheck European Integrated Project LSHG-CT-2004-503464). D.W.S. was partially supported by US National Institutes of Health (NIH) grant P41 RR013642. M.E.B. was partly supported by NIH grant R01 EB004155-03. S.P. was partially supported by NIH grant P41 RR13218. S.D. was supported by the Wellcome Trust. J.-K.H. was supported by the ENFIN European Network of Excellence (contract LSHG-CT-2005-518254) awarded to J.E. A.E.C. and A.F. were supported by NIH grant 5 RL1 CA133834-03. J.E.S. was supported by the British Heart Foundation (grant BS/06/001) and the BBSRC (grant E003443). This work was funded in part through the NIH Roadmap for Medical Research grants U54 RR021813 (D.W.S.) and U54 EB005149 (S.P.). Information on the US National Centers for Biomedical Computing can be obtained from http://nihroadmap.nih.gov/bioinformatics/.

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Walter, T., Shattuck, D., Baldock, R. et al. Visualization of image data from cells to organisms. Nat Methods 7 (Suppl 3), S26–S41 (2010). https://doi.org/10.1038/nmeth.1431

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