Glaucoma detection system

Abstract

Glaucoma is an eye disease which could lead to irreversible blindness if not treated early. Like many other eye diseases, glaucoma in its early stages doesn't usually present visible symptoms and also, its early stage symptoms can show some similarity to some other eye diseases. Traditionally, the diagnosis of such glaucoma requires very specialized personnel (ophthalmologists) and very expensive tests, as well as expensive equipment to aid in the medical diagnosis, which is not available in every community. Also, people in most communities do not have access to these specialized personnel to carry out these diagnoses for them. The Glaucoma Detection System (GDS) offers several advantages over traditional glaucoma diagnosis methods. It eliminates the need for specialized equipment and expensive tests, making it more accessible to a wider population. By leveraging deep learning, the tool provides reliable and consistent results, reducing the risk of missed or delayed diagnoses. Moreover, it overcomes the shortage of ophthalmologists in underserved areas by enabling early identification of glaucoma and facilitating timely interventions. The Glaucoma Detection System, automates the process of diagnosing glaucoma in retinal fundus eye images through the use of a powerful deep learning algorithm called VGG16. Deep learning techniques have proven to be more accurate than traditional machine learning methods on a variety of tasks and thus justifying our need to apply them. This improved efficiency will consequently lead to a reduction in errors in diagnosis.