High signal-to-noise ratio reconstruction of low bit-depth optical coherence tomography using deep learning-Reference-Cited by-同舟云学术

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High signal-to-noise ratio reconstruction of low bit-depth optical coherence tomography using deep learning

Published:2020-11-15 Issue:12 Volume:25 Page:
ISSN:1083-3668
Container-title:Journal of Biomedical Optics
language:
Short-container-title:J. Biomed. Opt.

Author:

Hao Qiangjiang¹,Zhou Kang¹,Yang Jianlong¹,Hu Yan²,Chai Zhengjie¹,Ma Yuhui¹,Liu Gangjun³,Zhao Yitian¹,Gao Shenghua⁴,Liu Jiang¹

Affiliation:

1. Chinese Academy of Sciences, Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials

2. Southern University of Science and Technology, Department of Computer Science and Engineering, Shenz

3. Shenzhen Bay Laboratory, Shenzhen

4. ShanghaiTech University, School of Information Science and Technology, Shanghai

Publisher

SPIE-Intl Soc Optical Eng

Subject

Biomedical Engineering,Atomic and Molecular Physics, and Optics,Biomaterials,Electronic, Optical and Magnetic Materials

Reference34 articles.

1. The ecosystem that powered the translation of OCT from fundamental research to clinical and commercial impact [Invited]

2. Optical coherence tomography – current and future applications

3. High-speed OCT light sources and systems [Invited]

4. Methodological Challenges of Deep Learning in Optical Coherence Tomography for Retinal Diseases: A Review

5. Compressive sensing in medical imaging

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