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Computer-aided imaging

Deep learning to predict microscope images

Nature Methodsvolume 15pages868870 (2018) | Download Citation

A type of neural network first described in 2015 can be trained to translate between images of the same field of view acquired by different modalities. Trained networks can use information inherent in grayscale images of cells to predict fluorescent signals.

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We are grateful to J. Markoff, J. Yosinski, J. Clune, G. Johnson, M. Maleckar, W. Peria, and other colleagues for useful communications and insight, and for support from R21 CA223901 to R.B. and U54 CA132831 (NMSU/FHCRC Partnership for the Advancement of Cancer Research) to R.B. and L.B.

Author information


  1. Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    • Roger Brent
  2. Klipsch School of Electrical and Computer Engineering, New Mexico State University, Las Cruces, NM, USA

    • Laura Boucheron


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Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Roger Brent.

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Further reading

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    Histochemistry and Cell Biology (2019)

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