Classification of Color Fundus Photographs Using Fusion Extracted Features and Customized CNN Models

This study focuses on overcoming challenges in classifying eye diseases using color fundus photographs by leveraging deep learning techniques, aiming to enhance early detection and diagnosis accuracy. We utilized a dataset of 6392 color fundus photographs across eight disease categories, which was l...

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Detalles Bibliográficos
Autores principales: Wang, Jing-Zhe, Lu, Nan-Han, Du, Wei-Chang, Liu, Kuo-Ying, Hsu, Shih-Yen, Wang, Chi-Yuan, Chen, Yun-Ju, Chang, Li-Ching, Twan, Wen-Hung, Chen, Tai-Been, Huang, Yung-Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10418900/
https://www.ncbi.nlm.nih.gov/pubmed/37570467
http://dx.doi.org/10.3390/healthcare11152228

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10418900/
https://www.ncbi.nlm.nih.gov/pubmed/37570467
http://dx.doi.org/10.3390/healthcare11152228

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