About this document
Glaucoma Detection via Fundus Imaging by sadiy22719 is a document available to read on EtoBox.
The project focuses on developing an image processing technique for detecting glaucoma through retinal fundus images, achieving 97.5% accuracy using features like Cup to Disc Ratio (CDR). It outlines the challenges of current detection methods and proposes a deep learning-based system utilizing the VGG16 algorithm for improved diagnosis. The system aims for early detection, non-invasive screening, and automated analysis to assist clinicians in managing glaucoma effectively.
- Author
- sadiy22719
- Language
- EN