Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2012 Jun 28;9(7):697-710.
doi: 10.1038/nmeth.2084.

Biological imaging software tools

Kevin W Eliceiri  1 , Michael R Berthold, Ilya G Goldberg, Luis Ibáñez, B S Manjunath, Maryann E Martone, Robert F Murphy, Hanchuan Peng, Anne L Plant, Badrinath Roysam, Nico Stuurman, Jason R Swedlow, Pavel Tomancak, Anne E Carpenter
Affiliations

Biological imaging software tools

Kevin W Eliceiri et al. Nat Methods. .

Erratum in

  • Nat Methods. 2012 Oct;9(10):1031. Stuurmann, Nico [corrected to Stuurman, Nico]

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.

PubMed Disclaimer

Figures

Figure 1
Figure 1. Image Acquisition
Legend: Image acquisition spans a range of complexity and variation.
Figure 2
Figure 2. Image Storage
Legend: Options for image storage span a range of complexity and variation.
Figure 3
Figure 3. Image Analysis and Visualization
Legend: Image analysis and visualization span a range of complexity and variation.
Figure 4
Figure 4. Segmentation, tracking and feature extraction in multidimensional images
Actual screen view illustrating the series of image analysis steps starting from a multi-channel multi-photon time-lapse movie culminating in a bio-informatic profiling of the extracted spatio-temporal data, using the FARSIGHT toolkit. This movie (Courtesy Dr. Ellen Robey, UC Berkeley) recorded the three-dimensional (3-D) movements of thymocytes in an ex-vivo preparation of a live developing mouse thymus at two-minute intervals, with wild-type thymocytes displayed in cyan, F5 thymocytes in green, and dendritic cells in violet. (a) The first step is cell segmentation, shown as an orthogonal (x, y, z, t) view. Cells are delineated, and identified with numbers that correspond to rows of a table of cell measurements (not shown). The cell tracking results are displayed in multiple ways in panels B and C. (b) "Beads on strings" view showing the 3-D movement paths of cells for detecting anomalies. (c) "3-D kymograph view" showing the same movement paths overlaid on a spatio-temporal (x, y, t) projection for convenience of assessing cell tracking accuracy. (d) Histogram of cell morphological measurements (size). (e) Scatter plots provide a visual cytometric summary of pairs of measurements. (f) Coifman bi-cluster plots organize the cell data into groups based on the cytometric data. (g) Histogram of cell tracking measurements (track tortuosity).(h) Scatter plot view of pairs of cell-track measurements. (i) Coifman bi-cluster plot organizing the cell tracks into groups based on the track-based measurements. The bi-cluster modules are courtesy of Drs. Ronald Coifman (Yale University), and Lawrence Carin (Duke University).
Figure 5
Figure 5. BioImaging Libraries and Toolkits
Legend: Bioimaging libraries and toolkits are available to cover a range of functionalities.
Figure 6
Figure 6. Machine Learning
Legend: Application areas where machine learning is used in bioimaging.
Figure 7
Figure 7. Workflow Systems
Legend: Benefits of using a workflow system.
See this image and copyright information in PMC

References

    1. Peng H. Bioimage informatics: a new area of engineering biology. Bioinformatics. 2008;24:1827–1836. - PMC - PubMed
    1. Gustafsson MG. Nonlinear structured-illumination microscopy: wide-field fluorescence imaging with theoretically unlimited resolution. Proc. Natl. Acad. Sci. USA. 2005;102:13081–13086. - PMC - PubMed
    1. Huang B, Wang W, Bates M, Zhuang X. Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy. Science. 2008;319:810–813. - PMC - PubMed
    1. Hess ST, Girirajan TP, Mason MD. Ultra-high resolution imaging by fluorescence photoactivation localization microscopy. Biophys. J. 2006;91:4258–4272. - PMC - PubMed
    1. Jones SA, Shim SH, He J, Zhuang X. Fast, three-dimensional super-resolution imaging of live cells. Nat. Methods. 2011;8:499–508. - PMC - PubMed

Publication types

MeSH terms