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,...

Description complète

Détails bibliographiques

Auteurs principaux:	Aqib Ali, Salman Qadri, Wali Khan Mashwani, Wiyada Kumam, Poom Kumam, Samreen Naeem, Atila Goktas, Farrukh Jamal, Christophe Chesneau, Sania Anam, Muhammad Sulaiman
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2020-05-01
Collection:	Entropy
Sujets:	diabetic retinopathy clustering segmentation hybrid features classification
Accès en ligne:	https://www.mdpi.com/1099-4300/22/5/567
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!