Deep learning massively accelerates super-resolution localization microscopy

By Ouyang Wei, A. Aristov, M. Lelek, Xian Hao, Christophe Zimmer. Nature Biotechnology, 2018

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Machine learning and applications in ultrafast photonics (2020, background): “Particular areas of success include in the design of nanomaterials and structures with specific target properties 9–11 , label-free cell classification 12 , super-resolution microscopy 13,14 , quantum optics 15 and optical communications 16–18 .”
Inference in artificial intelligence with deep optics and photonics (2020, background): “Applications of deep learning in optical microscopy cover brightfield microscopy 80 , lensless microscopy 72,81,87 , fluorescence microscopy 82,83,85,86,88,89 , super-resolution microscopy 80,86,90–92 , confocal microscopy 85,86,93 , structured illumination microscopy 86 and many others 84,94–96 .”
State-of-the-art review on deep learning in medical imaging. (2019, methodology): “Recently, DL has also been applied to enhance super-resolution localization microscopy (53), Resolution enhancement of wide-field interferometric microscopy (54) and rapid autofocusing in whole slide imaging (55).”