自适应光学显微中基于深度学习的复杂波前探测方法

胡淑文; 胡乐佳; 龚薇; 李政翰; 斯科

doi:10.1631/FITEE.2000422

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自适应光学显微中基于深度学习的复杂波前探测方法

常规文章 | Updated：2022-06-06

- 自适应光学显微中基于深度学习的复杂波前探测方法
- Deep learning based wavefront sensor for complex wavefront detection in adaptive optical microscopes
- 信息与电子工程前沿（英文） 2021年22卷第10期页码：1277-1288
- Affiliations：
  
  Department of Neurology of the First Affiliated Hospital, State Key Laboratory of Modern Optical Instrumentation, Zhejiang University School of Medicine, Hangzhou 310009, China
  College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China
  Research Units for Emotion and Emotion Disorders, Chinese Academy of Medical Sciences, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou 310058, China
- Author bio：
  
  [ "", "Shuwen HU, first author of this invited paper, received her BS degree from Tianjin University, China. She is currently a master degree candidate at the College of Optical Science and Engineering, Zhejiang University, China. Her research interests include adaptive optics, machine learning, and deep tissue imaging" ]
  [ "", "Wei GONG, corresponding author of this invited paper, is a PI at Zhejiang University School of Medicine, China. She received her BS and MS degrees from Zhejiang University, China, and her PhD degree from the National University of Singapore, Singapore. She is a special expert of the Ministry of Education (MOE) and the Outstanding Youth of Zhejiang Province. Her research interests include biomedical imaging, optical clearing, and artificial intelligence in biomedicine. E-mail: weigong@zju.edu.cn" ]
  [ "", "Ke SI, corresponding author of this invited paper, is a professor at the College of Optical Science and Engineering, Zhejiang University, China, and a joint professor at Zhejiang University School of Medicine. He is the Vice Director of MOE Frontier Science Center for Brain Science and Brain-Machine Integration, and the Vice Dean of the School of Brain Science and Brain Medicine. He is now a corresponding expert of Front Inform Technol Electron Eng. His research focuses on biophotonics, deep tissue imaging, adaptive optics, and optogenetics" ]
- Funds：
  
  the National Natural Science Foundation of China(61735016);the National Natural Science Foundation of China(81771877);the National Natural Science Foundation of China(61975178);the Zhejiang Provincial Natural Science Foundation of China(LR20F050002);the Key R&D Program of Zhejiang Province, China(2021C03001);the CAMS Innovation Fund for Medical Sciences, China(2019-I2M-5-057);the Fundamental Research Funds for the Central Universities, China
- DOI：10.1631/FITEE.2000422
  中图分类号： O439
- 收稿：2020-08-21，
  
  修回：2021-;1-25，
  
  网络出版：2021-03-29，
  
  纸质出版：2021-10
- Accepted：
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胡淑文, 胡乐佳, 龚薇, 等. 自适应光学显微中基于深度学习的复杂波前探测方法[J]. 信息与电子工程前沿（英文）, 2021,22(10):1277-1288.

Shuwen HU, Lejia HU, Wei GONG, et al. Deep learning based wavefront sensor for complex wavefront detection in adaptive optical microscopes[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(10): 1277-1288.
胡淑文, 胡乐佳, 龚薇, 等. 自适应光学显微中基于深度学习的复杂波前探测方法[J]. 信息与电子工程前沿（英文）, 2021,22(10):1277-1288. DOI： 10.1631/FITEE.2000422.

Shuwen HU, Lejia HU, Wei GONG, et al. Deep learning based wavefront sensor for complex wavefront detection in adaptive optical microscopes[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(10): 1277-1288. DOI： 10.1631/FITEE.2000422.

摘要

Shack-Hartmann波前传感器（SHWS）是自适应光学显微镜中用于波前传感的重要工具。然而，由复杂波前相位分布引起的畸变点阵限制了其探测性能。本文提出一种基于深度学习的波前探测方法，该方法结合了基于点扩散函数图像的泽尼克（Zernike）系数估计和波前相位分布拼接。该方法不仅仅使用每个子孔径的质心位移，而是通过子孔径的点扩散函数分布估计局部波前对应的Zernike系数，然后拼接局部波前进行重建。本文所提方法可实现高精度的复杂波前检测，获得的波前残差均方根误差值显著降低，在自适应光学显微中具有极大应用潜力。

Abstract

The Shack-Hartmann wavefront sensor (SHWS) is an essential tool for wavefront sensing in adaptive optical microscopes. However

the distorted spots induced by the complex wavefront challenge its detection performance. Here

we propose a deep learning based wavefront detection method which combines point spread function image based Zernike coefficient estimation and wavefront stitching. Rather than using the centroid displacements of each micro-lens

this method first estimates the Zernike coefficients of local wavefront distribution over each micro-lens and then stitches the local wavefronts for reconstruction. The proposed method can offer low root mean square wavefront errors and high accuracy for complex wavefront detection

and has potential to be applied in adaptive optical microscopes.

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