The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Content-aware image restoration: pushing the limits of fluorescence microscopy
Open accessAbstract
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. Content-aware image restoration (CARE) uses deep learning to improve microscopy images. CARE bypasses the trade-offs between imaging speed, resolution, and maximal light exposure that limit fluorescence imaging to enable discovery.
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Cites
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“This distinguishes them from conventional image restoration approaches such as deconvolution [17, 45], where only a single restored intensity value is computed per pixel.”
BackgroundOn calibration of modern neural networks
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Metadata
- Authors
- Weigert, M., Schmidt, U., Boothe, T., Müller, A., Dibrov, A., Jain, A., Wilhelm, B., Schmidt, D., Broaddus, C., Culley, S., Rocha-Martins, M., Segovia-Miranda, F., Norden, C., Henriques, R., Zerial, M., Solimena, M., Rink, J., Tomancak, P., Royer, L., Jug, F., & Myers, E. W.
- Venue
- Nature Methods
- Published
- 2018-11-26
- Volume
- 15
- Issue
- 12
- Pages
- 1090-1097
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2950501364
- Cited by
- 1,197
- References
- 11
- FWCI
- 48.48
- Type
- journal article
- Language
- en
- Open access
- green
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- Weigert, M., Schmidt, U., Boothe, T., Müller, A., Dibrov, A., Jain, A., Wilhelm, B., Schmidt, D., Broaddus, C., Culley, S., Rocha-Martins, M., Segovia-Miranda, F., Norden, C., Henriques, R., Zerial, M., Solimena, M., Rink, J., Tomancak, P., Royer, L., . . . Myers, E. W. (2018). Content-aware image restoration: pushing the limits of fluorescence microscopy. Nature Methods. https://doi.org/10.1038/s41592-018-0216-7
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