Quality improvement of adaptive optics retinal images using conditional adversarial networks

Author:

Li WanyueORCID,Liu Guangxing,He YiORCID,Wang Jing,Kong Wen,Shi GuohuaORCID

Funder

National Basic Research Program of China

Jiangsu Provincial Key Research and Development Program

National Natural Science Foundation of China

Youth Innovation Promotion Association of the Chinese Academy of Sciences

Strategic Priority Research Program of Chinese Academy of Sciences

Publisher

The Optical Society

Subject

Atomic and Molecular Physics, and Optics,Biotechnology

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Turbulence compensation with pix-to-pix generative adversarial networks in vector vortex beams;Physica Scripta;2024-09-09

2. Quantifying image quality in AOSLO images of photoreceptors;Biomedical Optics Express;2024-04-04

3. Semi-supervised generative adversarial learning for denoising adaptive optics retinal images;Biomedical Optics Express;2024-02-06

4. A Hybrid Approach for retinal image super-resolution;Biomedical Engineering Advances;2023-11

5. Retinal Image Restoration using Transformer and Cycle-Consistent Generative Adversarial Network;2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS);2022-11-22

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