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Fourier ring correlation simplifies image restoration in fluorescence microscopy.

Sami V KohoGiorgio TortaroloMarco CastelloTakahiro DeguchiAlberto DiasproGiuseppe Vicidomini
Published in: Nature communications (2019)
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.
Keyphrases
  • deep learning
  • single molecule
  • convolutional neural network
  • optical coherence tomography
  • high resolution
  • healthcare
  • machine learning
  • magnetic resonance
  • mass spectrometry
  • photodynamic therapy
  • finite element