Detection of Retinal Anatomical Structures and its Application to Image Quality Assessment - Michelassi, Rodrigo de Castro; Hirata, Nina S. T. (Anais Estendidos da Conference on Graphics, Patterns and Images (SIBGRAPI), 2025)
Given the general shortage of ophthalmologists in Brazil, automated retinal image screening emerges as a fundamental tool to promote early diagnosis of retinal diseases and prevent, for example, blindness. Motivated by this, we propose the use of YOLO-based object detection models to detect two retinal structures – the optic disc and the macular region – which play a crucial role in ophthalmological examinations. As a case study, based on detections performed on BRSET images, we determined the distances between the structures and the retinal edges. We found that the calculated distances do not always meet the minimum distance established in the Image Quality Assessment Image Field protocol. The results highlight the ability of YOLO-based models to reliably detect anatomical structures in retinal images and their potential to contribute to improving analyses that rely on these detections.