Abstract
The quality of super-resolution images obtained by single-molecule localization microscopy (SMLM) depends largely on the software used to detect and accurately localize point sources. In this work, we focus on the computational aspects of super-resolution microscopy and present a comprehensive evaluation of localization software packages. Our philosophy is to evaluate each package as a whole, thus maintaining the integrity of the software. We prepared synthetic data that represent three-dimensional structures modeled after biological components, taking excitation parameters, noise sources, point-spread functions and pixelation into account. We then asked developers to run their software on our data; most responded favorably, allowing us to present a broad picture of the methods available. We evaluated their results using quantitative and user-interpretable criteria: detection rate, accuracy, quality of image reconstruction, resolution, software usability and computational resources. These metrics reflect the various tradeoffs of SMLM software packages and help users to choose the software that fits their needs.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 717-724 |
| Number of pages | 8 |
| Journal | Nature Methods |
| Volume | 12 |
| Issue number | 8 |
| DOIs | |
| State | Published - Jul 30 2015 |
Bibliographical note
Funding Information:We thank N. Olivier for providing the experimental data and R. Nieuwenhuizen for his technical assistance in running the Fourier ring correlation. We thank also P. Thévenaz for critical reading and for his assistance in writing the manuscript. We thank the participants in the ISBI 2013 localization microscopy challenge: S. Anthony, S. Andersson, T. Ashley, D. Baddeley, K. Bennett, J. Boulanger, N. Brede, L. Dai, L. Fiaschi, F. Gruell, G. Hagen, R. Henriques, A. Herbert, S. Holden, E. Hoogendoorn, B. Huang, Z.-L. Huang, A. Kechkar, K. Kim, M. Kirchgessner, U. Koethe, P. Krizek, M. Lakadamyali, Y. Li, K. Lidke, R. McGorty, L. Muresan, R. Parthasarathy, B. Rieger, H. Rouault, M. Sauer, J.-B. Sibarita, I. Smal, A. Small, S. Stahlheber, Y. Tang, Y. Wang, S. Watanabe, S. Wolter, J.C. Ye and C. Zimmer. This work was supported by the Biomedical Imaging Group, the School of Engineering at the Ecole Polytechnique Fédérale de Lausanne, the European Research Council (ERC) FUN-SP project (267439), the ERC Starting Grant PALMassembly (243016) and the Eurobioimaging Project (WP11).
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