Graph-enhanced deep learning for diabetic retinopathy diagnosis: A quality-aware and uncertainty-driven approach
Fig 3
Comparison of normalized confusion matrices for multiclass DR classification on the APTOS and Messidor-2 datasets using different preprocessing methods: Our pipeline with No Preprocessing (left), CLAHE preprocessing (middle), and Ben-Graham preprocessing (right).
MobileViT model on APTOS2019 dataset shows excellent performance, with minimal misclassification and high precision-recall (AP=1.00). DenseNet169 on the Messidor-2 dataset achieves high accuracy.