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) |
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源语言 | 繁体中文 |
文章编号 | 1611004 |
期刊 | Laser and Optoelectronics Progress |
卷 | 61 |
期 | 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