GLAUCOMA DETECTION USING IMAGE PROCESSING WITH MATLAB SOFTWARE

This research focuses on advancing glaucoma detection through digital processing of fundus images using MATLAB. Glaucoma is a leading cause of irreversible blindness, necessitating early and accurate diagnosis for effective intervention. Leveraging the capabilities of MATLAB, this study proposes a robust image processing framework to enhance the detection accuracy of glaucoma from fundus images. The methodology involves preprocessing techniques, feature extraction, and classification algorithms to analyze key structural indicators associated with glaucomatous changes. The developed MATLAB-based system aims to provide a reliable and efficient tool for early glaucoma diagnosis, contributing to improved patient outcomes. The proposed methodology showcases promising results in terms of sensitivity and specificity, demonstrating its potential as a valuable diagnostic aid in ophthalmic clinical settings. The utilization of digital processing techniques in conjunction with MATLAB presents a novel and accessible approach for enhancing glaucoma detection, ultimately facilitating timely and effective management of this sight-threatening condition.

Keywords: Glaucoma, Open angle glaucoma, angle closure glaucoma, fundus images, CDR, smoothing filter.