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Journal of Innovative Optical Health Sciences, Volume. 16, Issue 3, 2230016(2023)

Deep-learning-based methods for super-resolution fluorescence microscopy

Jianhui Liao1... Junle Qu1, Yongqi Hao2,* and Jia Li1,** |Show fewer author(s)
Author Affiliations
  • 1Shenzhen Key Laboratory of Photonics and Biophotonics, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, P. R. China
  • 2NARI Group Corporation (State Grid Electric Power Research Institute), NARI Technology Co., Ltd., Nanjing 211106, P. R. China
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    Jianhui Liao, Junle Qu, Yongqi Hao, Jia Li. Deep-learning-based methods for super-resolution fluorescence microscopy[J]. Journal of Innovative Optical Health Sciences, 2023, 16(3): 2230016

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    Paper Information

    Category: Research Articles

    Received: Sep. 6, 2022

    Accepted: Oct. 30, 2022

    Published Online: May. 25, 2023

    The Author Email: Hao Yongqi (haoyongqi@sgepri.sgcc.com.cn), Li Jia (jli@szu.edu.cn)

    DOI:10.1142/S1793545822300166

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology