Giovanni Rubegni

Smartphone-Based Automated Quantification of Bulbar Conjunctival Hyperemia Using Vessel Density Mapping

Purpose: To develop a smartphone application (Conjunctiva VD) that objectively quantifies bulbar conjunctival hyperemia by estimating the conjunctival vessel density (VD) within a user-defined region of interest (ROI). Methods: A total of 100 conjunctival images from 2 public dat...

Machine Learning-Based Classification of Retinitis Pigmentosa from Color Fundus Images: A Reproducible Benchmark and Screening-Oriented Pipeline

Retinitis pigmentosa (RP) is a rare inherited retinal disorder in which fundus changes may be subtle and heterogeneous, limiting detection from color fundus images. This study evaluated multiple machine learning architectures for binary-RP versus healthy-control classification, a...