Frontiers in Physics (Nov 2021)

Learning-Based Image Transport Through Disordered Optical Fibers With Transverse Anderson Localization

  • Jian Zhao,
  • Jian Zhao,
  • Xiaowen Hu,
  • Stefan Gausmann,
  • Jose Enrique Antonio-Lopez,
  • Rodrigo Amezcua Correa,
  • Axel Schülzgen

DOI
https://doi.org/10.3389/fphy.2021.710351
Journal volume & issue
Vol. 9

Abstract

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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.

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