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Title: Deep learning assisted optical wavefront shaping in disordered medium
Authors: Luo, Yunqi
Li, Huanhao
Zhang, Ruochong
Lai, Puxiang
Zheng, Yuanjin
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2019
Source: Luo, Y., Li, H., Zhang, R., Lai, P., & Zheng, Y. (2019). Deep learning assisted optical wavefront shaping in disordered medium. Proceedings of SPIE - Adaptive Optics and Wavefront Control for Biological Systems V, 10886, 1088612-. doi:10.1117/12.2504425
Abstract: Wavefront shaping (WFS) has been put forward several years ago to break the limitation caused by optical scattering in inhomogeneous medium, and realize optical focusing in disordered medium like biological tissues. However, usually, with traditional methods, WFS is time consuming and not cost efficient since it requires long time to obtain the information of the scattering medium. Here we propose the deep learning assisted wavefront shaping, which uses deep neural networks to predict the desired input optical modes that are needed to realize focusing after light passes through a scattering medium. Simulation results show that the pre-trained neural network is able to map output optical modes to input modes. Compared with previous methods which use iterative optimization, our method realizes a focused speckle pattern with the help of deep learning, which will definitely reduce complexity and time spent in optimization. Experiments will be conducted soon.
ISBN: 9781510624146
DOI: 10.1117/12.2504425
Rights: Copyright 2019 Society of Photo-Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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