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Second Harmonic Imaging Enhanced by Deep Learning Decipher
ACS Photonics ( IF 7 ) Pub Date : 2021-05-26 , DOI: 10.1021/acsphotonics.1c00395
Weiru Fan 1 , Tianrun Chen 1 , Eddie Gil 2 , Shiyao Zhu 1 , Vladislav Yakovlev 2 , Da-Wei Wang 1, 3 , Delong Zhang 1
Affiliation  

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 and high robustness against noise, facilitating numerous applications from biological imaging to wavefront sensing.

中文翻译:

深度学习解密增强二次谐波成像

波前传感和重建广泛用于自适应光学、像差校正和高分辨率光学相位成像。传统上,干涉和/或微透镜阵列用于将光学相位转换为强度变化。失真波前的直接成像通常会导致具有低对比度和低灵敏度的复杂相位检索。在这里,开发了一种新型非线性光学编码方法,并使用光学二次谐波生成来锐化探测光束携带的相位信息,并通过实验证明了这一方法。通过设计和实现一个深度神经网络,我们展示了由深度学习解密 (SHIELD) 增强的二次谐波成像,用于高效和弹性的相位检索。继承双光子显微优势,SHIELD演示单发、 以及对噪声的高度鲁棒性,促进了从生物成像到波前传感的众多应用。
更新日期:2021-06-17
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