Fourier ring correlation simplifies image restoration in fluorescence microscopy

Sami Koho (), Giorgio Tortarolo, Marco Castello, Takahiro Deguchi, Alberto Diaspro and Giuseppe Vicidomini ()
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Sami Koho: Istituto Italiano di Tecnologia
Giorgio Tortarolo: Istituto Italiano di Tecnologia
Marco Castello: Istituto Italiano di Tecnologia
Takahiro Deguchi: Istituto Italiano di Tecnologia
Alberto Diaspro: Istituto Italiano di Tecnologia
Giuseppe Vicidomini: Istituto Italiano di Tecnologia

Nature Communications, 2019, vol. 10, issue 1, 1-9

Abstract: Abstract Fourier ring correlation (FRC) has recently gained popularity among fluorescence microscopists as a straightforward and objective method to measure the effective image resolution. While the knowledge of the numeric resolution value is helpful in e.g., interpreting imaging results, much more practical use can be made of FRC analysis—in this article we propose blind image restoration methods enabled by it. We apply FRC to perform image de-noising by frequency domain filtering. We propose novel blind linear and non-linear image deconvolution methods that use FRC to estimate the effective point-spread-function, directly from the images. We show how FRC can be used as a powerful metric to observe the progress of iterative deconvolution. We also address two important limitations in FRC that may be of more general interest: how to make FRC work with single images (within certain practical limits) and with three-dimensional images with highly anisotropic resolution.

Date: 2019
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DOI: 10.1038/s41467-019-11024-z

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