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Fast, single-molecule localization that achieves theoretically minimum uncertainty

Nature Methods volume 7, pages 373–375 (2010)Cite this article

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Abstract

We describe an iterative algorithm that converges to the maximum likelihood estimate of the position and intensity of a single fluorophore. Our technique efficiently computes and achieves the Cramér-Rao lower bound, an essential tool for parameter estimation. An implementation of the algorithm on graphics processing unit hardware achieved more than 105 combined fits and Cramér-Rao lower bound calculations per second, enabling real-time data analysis for super-resolution imaging and other applications.

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Figure 1: Performance comparison on simulated data.
Figure 2: Basic concept of single-molecule localization via GPU implementation.

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Acknowledgements

This work was supported by the American Cancer Society (IRG-92-024) and the US National Institutes of Health (1P50GM085273-01A1). We thank M. Malik and I.T. Young for reading the manuscript.

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Authors and Affiliations

  1. Department of Imaging Science and Technology, Delft University of Technology, Delft, The Netherlands

    Carlas S Smith & Bernd Rieger

  2. Department of Physics and Astronomy, University of New Mexico, Albuquerque, New Mexico, USA

    Nikolai Joseph & Keith A Lidke

Authors
  1. Carlas S Smith
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  2. Nikolai Joseph
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  3. Bernd Rieger
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  4. Keith A Lidke
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Contributions

C.S.S. and K.A.L. worked out the algorithm and implementation; N.J. and K.A.L. performed the experiments; and B.R. and K.A.L. designed the research and wrote the paper.

Corresponding author

Correspondence to Keith A Lidke.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8, Supplementary Table 1, Supplementary Note 1 and Supplementary Data (PDF 363 kb)

Supplementary Software 1

Example MATLAB codes (ZIP 502 kb)

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Smith, C., Joseph, N., Rieger, B. et al. Fast, single-molecule localization that achieves theoretically minimum uncertainty. Nat Methods 7, 373–375 (2010). https://doi.org/10.1038/nmeth.1449

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