深 度 学 习 在 光 纤 成 像 中 的 应 用 进 展(特 邀)

Sun Jiawei, Chen Zhaoqing, Zhao Bin, Li Xuelong

科研成果: 期刊稿件文献综述同行评审

2 引用 (Scopus)

摘要

Fiber optic imaging technology can achieve high-resolution imaging in narrow areas due to the small size and flexibility of optical fibers. Fiber optic imaging can also be employed in biomedical research and industrial inspections. However, there are bottleneck problems in multi-core and multi-mode fiber imaging systems, limiting their resolution and accuracy. This paper briefly introduces representative research on the applications of deep learning to address these bottleneck problems in various fiber imaging modalities such as fluorescence imaging, quantitative phase imaging, speckle imaging, and multispectral imaging. Existing bottleneck in this interdisciplinary research field involving deep learning and fiber optic imaging are also discussed. Additionally, we envision the broad application prospects of intelligent fiber optic imaging systems.

投稿的翻译标题Advances in Deep Learning Based Fiber Optic Imaging (Invited)
源语言繁体中文
文章编号1611004
期刊Laser and Optoelectronics Progress
61
16
DOI
出版状态已出版 - 8月 2024

关键词

  • deep learning
  • endoscopy
  • fiber optic imaging
  • multi-core fiber
  • multi-mode fiber

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