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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Autores principales: Jian Zhao, Xiaowen Hu, Stefan Gausmann, Jose Enrique Antonio-Lopez, Rodrigo Amezcua Correa, Axel Schülzgen
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Lenguaje:EN
Publicado: Frontiers Media S.A. 2021
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Acceso en línea:https://doaj.org/article/fc47db35c3df4c2e918c15234b942a8a
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spelling 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)
institution DOAJ
collection DOAJ
language EN
topic transverse Anderson localization
optical fiber
imaging
deep learning
convolutional neural network
Physics
QC1-999
spellingShingle 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
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