Combination of Global Features for the Automatic Quality Assessment of Retinal Images. - Jorge Jiménez-García; Roberto Romero-Oraá; María García; María Isabel López Gálvez; Roberto Hornero (Entropy, 2019)

Entropy Rate Superpixel Classification for Automatic Red Lesion Detection in Fundus Images. - Roberto Romero-Oraá; Jorge Jiménez-García; María García; María Isabel López Gálvez; Javier Oraá-Pérez; Roberto Hornero (Entropy, 2019)

A robust method for the automatic location of the optic disc and the fovea in fundus images. - Roberto Romero-Oraá; María García; Javier Oraá-Pérez; María Isabel López; Roberto Hornero (Comput. Methods Programs Biomed., 2020)

Effective Fundus Image Decomposition for the Detection of Red Lesions and Hard Exudates to Aid in the Diagnosis of Diabetic Retinopathy. - Roberto Romero-Oraá; María García; Javier Oraá-Pérez; María Isabel López Gálvez; Roberto Hornero (Sensors, 2020)

Attention-based deep learning framework for automatic fundus image processing to aid in diabetic retinopathy grading. - Roberto Romero-Oraá; María Herrero-Tudela; María I. López; Roberto Hornero; María García (Comput. Methods Programs Biomed., 2024)

An explainable deep-learning model reveals clinical clues in diabetic retinopathy through SHAP. - María Herrero-Tudela; Roberto Romero-Oraá; Roberto Hornero; Gonzalo C. Gutiérrez-Tobal; María Isabel López; María García (Biomed. Signal Process. Control., 2025)