A novel approach for automatic classification of macular degeneration OCT images-Reference-Cited by-同舟云学术

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A novel approach for automatic classification of macular degeneration OCT images

Published:2024-08-20 Issue:1 Volume:14 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Pang Shilong,Zou Beiji,Xiao Xiaoxia,Peng Qinghua,Yan Junfeng,Zhang Wensheng,Yue Kejuan

Funder

2023 Hunan Traditional Chinese Medicine Scientific Research Project

Research Foundation of Education Bureau of Hunan Province, China

Hunan Provincial Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Link

https://www.nature.com/articles/s41598-024-70175-2.pdf

Reference33 articles.

1. Wong, W. L. et al. Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: A systematic review and meta-analysis. Lancet Glob. Health 2(2), e106–e116. https://doi.org/10.1016/S2214-109X(13)70145-1 (2014).

2. Klein, R. et al. Fifteen-year cumulative incidence of age-related macular degeneration: The Beaver Dam Eye Study. Ophthalmology 114(2), 253–262. https://doi.org/10.1016/j.ophtha.2006.10.040 (2007).

3. Zhang, J. et al. Diabetic macular edema: Current understanding, molecular mechanisms and therapeutic implications. Cells 11(21), 3362. https://doi.org/10.3390/cells11213362 (2022).

4. Rasti, R., Rabbani, H., Mehridehnavi, A. & Hajizadeh, F. Macular OCT classification using a multi-scale convolutional neural network ensemble. IEEE Trans. Med. Imaging 37(4), 1024–1034. https://doi.org/10.1109/TMI.2017.2780115 (2017).

5. Ferris, F. L., Fine, S. L. & Hyman, L. Age-related macular degeneration and blindness due to neovascular maculopathy. Arch. Ophthalmol. 102(11), 1640–1642. https://doi.org/10.1001/archopht.1984.01040031330019 (1984).

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