Support Tools for the Presumptive Diagnosis of Glaucoma, as Well as for Determining the Degree of Keratoconus Involvement, as Methods for Detection, Prevention, and Care of the Human Eye

This project addresses the critical need for implementing early and timely diagnostic methods for ocular diseases leading to visual impairment in Ecuador, specifically Glaucoma and Keratoconus. Glaucoma, the second leading cause of blindness globally, is often diagnosed late, resulting in irreversible damage. Keratoconus, a progressive corneal ectasia, also requires constant monitoring. The proposed solution focuses on developing a system based on digital processing of ocular images. Initially, an exhaustive literature review will be conducted using the analytical method to understand eye behavior and Intraocular Pressure (IOP) measurement techniques. Subsequently, the analytical method will be applied to select the most appropriate approach for image processing. The ultimate goal is to develop an optimized algorithm and software capable of characterizing key parameters for the presumptive early diagnosis of Glaucoma and visualizing the degree of Keratoconus affection. These results will be validated with clinical specialists, aiming to mitigate the impact of these conditions on the vulnerable population and strengthen prevention and control strategies.<br/><br/><b>Goal</b>: <br/>To perform digital image processing of the eye to characterize parameters that contribute to the presumptive early diagnosis of glaucoma and to determine the degree of keratoconus affection for implementing preventive and control measures.<br/><br/><b>Research lines</b>: <br/>Biomedicine