Machine Learning Based Automated Segmentation and Hybrid Feature Analysis for Diabetic Retinopathy Classification Using Fundus Image

The object of this study was to demonstrate the ability of machine learning (ML) methods for the segmentation and classification of diabetic retinopathy (DR). Two-dimensional (2D) retinal fundus (RF) images were used. The datasets of DR—that is, the mild, moderate, non-proliferative, proliferative,...

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Detalles Bibliográficos
Autores principales: Ali, Aqib, Qadri, Salman, Khan Mashwani, Wali, Kumam, Wiyada, Kumam, Poom, Naeem, Samreen, Goktas, Atila, Jamal, Farrukh, Chesneau, Christophe, Anam, Sania, Sulaiman, Muhammad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517087/
https://www.ncbi.nlm.nih.gov/pubmed/33286339
http://dx.doi.org/10.3390/e22050567

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517087/
https://www.ncbi.nlm.nih.gov/pubmed/33286339
http://dx.doi.org/10.3390/e22050567

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