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• W3093341607 abstract "Wavefront sensing and reconstruction are widely used for adaptive optics, aberration correction, and high-resolution optical phase imaging. Traditionally, interference and/or microlens arrays are used to convert the optical phase into intensity variation. Direct imaging of distorted wavefront usually results in complicated phase retrieval with low contrast and low sensitivity. Here, a novel nonlinear optical encoding approach has been developed and experimentally demonstrated using optical second harmonic generation to sharpen the phase information carried by the probe beam. By designing and implementing a deep neural network, we demonstrate the second harmonic imaging enhanced by a deep learning decipher (SHIELD) for efficient and resilient phase retrieval. Inheriting the advantages of two-photon microscopy, SHIELD demonstrates single-shot, reference-free, and video-rate phase imaging with sensitivity better than λ100 and high robustness against noise, facilitating numerous applications from biological imaging to wavefront sensing." @default.
• W3093341607 created "2020-10-22" @default.
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• W3093341607 date "2021-05-26" @default.
• W3093341607 modified "2023-10-16" @default.
• W3093341607 title "Second Harmonic Imaging Enhanced by Deep Learning Decipher" @default.
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• W3093341607 doi "https://doi.org/10.1021/acsphotonics.1c00395" @default.
• W3093341607 hasPublicationYear "2021" @default.
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