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Photonics Research, Volume. 12, Issue 3, 474(2024)

Deep learning-based optical aberration estimation enables offline digital adaptive optics and super-resolution imaging On the Cover

Chang Qiao1,2、†, Haoyu Chen3,4、†, Run Wang1、†, Tao Jiang3,4, Yuwang Wang5,6, and Dong Li3,4、*
Author Affiliations
  • 1Department of Automation, Tsinghua University, Beijing 100084, China
  • 2Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China
  • 3National Laboratory of Biomacromolecules, New Cornerstone Science Laboratory, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
  • 4College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
  • 5Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China
  • 6e-mail: wang-yuwang@mail.tsinghua.edu.cn
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    Citation counts are provided from Web of Science. The counts may vary by service, and are reliant on the availability of their data.
    The article is cited by 11 article(s) from Web of Science.
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    Chang Qiao, Haoyu Chen, Run Wang, Tao Jiang, Yuwang Wang, Dong Li, "Deep learning-based optical aberration estimation enables offline digital adaptive optics and super-resolution imaging," Photonics Res. 12, 474 (2024)

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    Paper Information

    Category: Imaging Systems, Microscopy, and Displays

    Received: Sep. 27, 2023

    Accepted: Dec. 20, 2023

    Published Online: Feb. 29, 2024

    The Author Email: Dong Li (lidong@ibp.ac.cn)

    DOI:10.1364/PRJ.506778

    CSTR:32188.14.PRJ.506778

    Topics

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