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  Content-aware image restoration: Pushing the limits of fluorescence microscopy.

Weigert, M., Schmidt, U., Boothe, T., Müller, A., Dibrov, A., Jain, A., et al. (2018). Content-aware image restoration: Pushing the limits of fluorescence microscopy. Nature Methods, 15(12), 1090-1097. doi:10.1038/s41592-018-0216-7.

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 Creators:
Weigert, M., Author
Schmidt, U., Author
Boothe, T., Author
Müller, A., Author
Dibrov, A., Author
Jain, A., Author
Wilhelm, B., Author
Schmidt, D., Author
Broaddus, C., Author
Culley, S., Author
Rocha-Martins, M., Author
Segovia-Miranda, F., Author
Norden, C., Author
Henriques, R., Author
Zerial, M., Author
Solimena, M., Author
Rink, J. C.1, Author              
Tomancak, P., Author
Royer, L., Author
Jug, F., Author
Myers, E. W., Author more..
Affiliations:
1Department of Tissue Dynamics and Regeneration, MPI for Biophysical Chemistry, Max Planck Society, ou_3181978              

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 Abstract: Fluorescence microscopy is a key driver of discoveries in the life sciences, with observable phenomena being limited by the optics of the microscope, the chemistry of the fluorophores, and the maximum photon exposure tolerated by the sample. These limits necessitate trade-offs between imaging speed, spatial resolution, light exposure, and imaging depth. In this work we show how content-aware image restoration based on deep learning extends the range of biological phenomena observable by microscopy. We demonstrate on eight concrete examples how microscopy images can be restored even if 60-fold fewer photons are used during acquisition, how near isotropic resolution can be achieved with up to tenfold under-sampling along the axial direction, and how tubular and granular structures smaller than the diffraction limit can be resolved at 20-times-higher frame rates compared to state-of-the-art methods. All developed image restoration methods are freely available as open source software in Python, FIJI, and KNIME.

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Language(s): eng - English
 Dates: 2018-11-262018
 Publication Status: Published in print
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 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41592-018-0216-7
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Title: Nature Methods
Source Genre: Journal
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Pages: - Volume / Issue: 15 (12) Sequence Number: - Start / End Page: 1090 - 1097 Identifier: -