Super-resolution microscopy opened diverse new avenues of research by overcoming the resolution limit imposed by diffraction. Exploitation of the fluorescent emission of individual fluorophores made it possible to reveal structures beyond the diffraction limit. To accurately determine the resolution achieved during imaging is challenging with existing metrics. Here, we propose a method for assessing the resolution of individual super-resolved images based on image partial phase autocorrelation. The algorithm is model-free and does not require any user-defined parameters. We demonstrate its performance on a wide variety of imaging modalities, including diffraction-limited techniques. Finally, we show how our method can be used to optimize image acquisition and post-processing in super-resolution microscopy.
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The MATLAB soruce code, the ImageJ plugin and the source Java code are publicly available on https://github.com/Ades91/ImDecorr.git or may be requested from the authors.
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The authors would like to thank T. Lukes and T. Laser for insightful discussions. We also thank H. Deschout, M. Muller, T. Huser and M. Sauer for sharing SOFI and SIM data. We also thank J. Schmied and P. Tinnefeld for sharing GATTAquant nanoruler data and N. Bantherle and A. Planchette for proofreading. This project has been funded in part by the Horizon 2020 research and innovation program of the European Union via grant 686271/SEFRI 16.0047. K.S.G. acknowledges support from the Horizon 2020 Framework Program of the European Union under the Marie Skłodowska-Curie grant agreement no. 750528 and thanks the NVIDIA Corporation for the donation of a Titan Xp GPU. A.D. and A.R. acknowledge support from the Zeiss IDEAS center. We would like to thank the EPFL BioImaging & Optics Core Facility (EPFL-BIOP) for access to confocal and STED microscopes.
The authors declare no competing interests.
Peer review information: Rita Strack was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
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Descloux, A., Grußmayer, K.S. & Radenovic, A. Parameter-free image resolution estimation based on decorrelation analysis. Nat Methods 16, 918–924 (2019) doi:10.1038/s41592-019-0515-7