The Glaucoma is a group of eye diseases causing optic nerve damage, as it has no symptoms and if not detected at an early stage it may cause permanent blindness. Glaucoma progression precedes some structural damage to the retina are the marked symptoms of Glaucoma, which the second leading cause of blindness worldwide, early diagnosing and treatment can prevent progression of the disease and preventing blindness, where the diagnose suffer from the subjectivity of human due to experience, fatigue factor etc.
This special issue presents a detection algorithm motivated by the evaluation guidelines used by ophthalmologists for the diagnosis of glaucoma. The proposed strategy will focus on features gathered from retinal fundus images, which are among one of the biomedical imaging techniques to analyze the internal structure of retina, with the widespread adoption of higher quality, data, less expensive compared with the other used techniques, and can used to diagnose another diseases like Diabetic retinopathy.
Finally, this special issue main aim is to present a Glaucoma diagnosis algorithm with high accuracy can help in minimize the miss-detection rate and help in early diagnosis and treatment, reduce the workload of ophthalmologists which can significantly improve the chance of managing the Glaucoma disease.