Intensity and phase imaging through scattering media via deep despeckle complex neural networks

Shuai Liu, Peng Li, Hao Sha, Jiuyang Dong, Yue Huang, Yanjing Zhao, Xuri Yao, Qin Peng, Xiu Li, Xing Lin*, Yongbing Zhang

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

5 引用 (Scopus)

摘要

The existence of a scattering medium causes the degeneration of intensity and phase information, especially in biological imaging. The present techniques to address this challenge only focus on the reconstruction of intensity information, yet few attempts have tried to recover the phase information. We propose a method to simultaneously predict both intensity and phase information from a speckle image employing a deep despeckle complex neural network (DespeckleNet). By combining the advantages of both the complex network and the generative adversarial network framework, our method enables the high contrast single-shot imaging of complicated biological samples through scattering media without labeling. Various experiments demonstrate the superior reconstruction and generalization performance of our method under multiple types of biological samples with different scattering media. We also provide the real-time observation of living cellular activities without any contaminations or damages to the cells. Our method offers simple yet effective imaging through scattering media and paves the way for real-time unlabeled biological imaging.

源语言英语
文章编号107196
期刊Optics and Lasers in Engineering
159
DOI
出版状态已出版 - 12月 2022

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