Learning-Based Image Transport Through Disordered Optical Fibers With Transverse Anderson Localization
Fiber-optic imaging systems play a unique role in biomedical imaging and clinical practice due to their flexibilities of performing imaging deep into tissues and organs with minimized penetration damage. Their imaging performance is often limited by the waveguide mode properties of conventional opti...
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Frontiers Media S.A.
2021
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oai:doaj.org-article:fc47db35c3df4c2e918c15234b942a8a2021-11-04T08:44:46ZLearning-Based Image Transport Through Disordered Optical Fibers With Transverse Anderson Localization2296-424X10.3389/fphy.2021.710351https://doaj.org/article/fc47db35c3df4c2e918c15234b942a8a2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fphy.2021.710351/fullhttps://doaj.org/toc/2296-424XFiber-optic imaging systems play a unique role in biomedical imaging and clinical practice due to their flexibilities of performing imaging deep into tissues and organs with minimized penetration damage. Their imaging performance is often limited by the waveguide mode properties of conventional optical fibers and the image reconstruction method, which restrains the enhancement of imaging quality, transport robustness, system size, and illumination compatibility. The emerging disordered Anderson localizing optical fibers circumvent these difficulties by their intriguing properties of the transverse Anderson localization of light, such as single-mode-like behavior, wavelength independence, and high mode density. To go beyond the performance limit of conventional system, there is a growing interest in integrating the disordered Anderson localizing optical fiber with deep learning algorithms. Novel imaging platforms based on this concept have been explored recently to make the best of Anderson localization fibers. Here, we review recent developments of Anderson localizing optical fibers and focus on the latest progress in deep-learning-based imaging applications using these fibers.Jian ZhaoJian ZhaoXiaowen HuStefan GausmannJose Enrique Antonio-LopezRodrigo Amezcua CorreaAxel SchülzgenFrontiers Media S.A.articletransverse Anderson localizationoptical fiberimagingdeep learningconvolutional neural networkPhysicsQC1-999ENFrontiers in Physics, Vol 9 (2021) |
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transverse Anderson localization optical fiber imaging deep learning convolutional neural network Physics QC1-999 |
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transverse Anderson localization optical fiber imaging deep learning convolutional neural network Physics QC1-999 Jian Zhao Jian Zhao Xiaowen Hu Stefan Gausmann Jose Enrique Antonio-Lopez Rodrigo Amezcua Correa Axel Schülzgen Learning-Based Image Transport Through Disordered Optical Fibers With Transverse Anderson Localization |
description |
Fiber-optic imaging systems play a unique role in biomedical imaging and clinical practice due to their flexibilities of performing imaging deep into tissues and organs with minimized penetration damage. Their imaging performance is often limited by the waveguide mode properties of conventional optical fibers and the image reconstruction method, which restrains the enhancement of imaging quality, transport robustness, system size, and illumination compatibility. The emerging disordered Anderson localizing optical fibers circumvent these difficulties by their intriguing properties of the transverse Anderson localization of light, such as single-mode-like behavior, wavelength independence, and high mode density. To go beyond the performance limit of conventional system, there is a growing interest in integrating the disordered Anderson localizing optical fiber with deep learning algorithms. Novel imaging platforms based on this concept have been explored recently to make the best of Anderson localization fibers. Here, we review recent developments of Anderson localizing optical fibers and focus on the latest progress in deep-learning-based imaging applications using these fibers. |
format |
article |
author |
Jian Zhao Jian Zhao Xiaowen Hu Stefan Gausmann Jose Enrique Antonio-Lopez Rodrigo Amezcua Correa Axel Schülzgen |
author_facet |
Jian Zhao Jian Zhao Xiaowen Hu Stefan Gausmann Jose Enrique Antonio-Lopez Rodrigo Amezcua Correa Axel Schülzgen |
author_sort |
Jian Zhao |
title |
Learning-Based Image Transport Through Disordered Optical Fibers With Transverse Anderson Localization |
title_short |
Learning-Based Image Transport Through Disordered Optical Fibers With Transverse Anderson Localization |
title_full |
Learning-Based Image Transport Through Disordered Optical Fibers With Transverse Anderson Localization |
title_fullStr |
Learning-Based Image Transport Through Disordered Optical Fibers With Transverse Anderson Localization |
title_full_unstemmed |
Learning-Based Image Transport Through Disordered Optical Fibers With Transverse Anderson Localization |
title_sort |
learning-based image transport through disordered optical fibers with transverse anderson localization |
publisher |
Frontiers Media S.A. |
publishDate |
2021 |
url |
https://doaj.org/article/fc47db35c3df4c2e918c15234b942a8a |
work_keys_str_mv |
AT jianzhao learningbasedimagetransportthroughdisorderedopticalfiberswithtransverseandersonlocalization AT jianzhao learningbasedimagetransportthroughdisorderedopticalfiberswithtransverseandersonlocalization AT xiaowenhu learningbasedimagetransportthroughdisorderedopticalfiberswithtransverseandersonlocalization AT stefangausmann learningbasedimagetransportthroughdisorderedopticalfiberswithtransverseandersonlocalization AT joseenriqueantoniolopez learningbasedimagetransportthroughdisorderedopticalfiberswithtransverseandersonlocalization AT rodrigoamezcuacorrea learningbasedimagetransportthroughdisorderedopticalfiberswithtransverseandersonlocalization AT axelschulzgen learningbasedimagetransportthroughdisorderedopticalfiberswithtransverseandersonlocalization |
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1718445059690463232 |