Abstract
Glaucoma is a very dangerous disease which is increasing alarmingly year by year. Often, people do not realize the severity or who is affected and also do not get to know the signs. The ganglia cells present in the retina of eye are affected due to the glaucoma, and it will lead to loss of eyesight. The main reason behind this disease is the increase of the intra-ocular pressure inside the eye which also damages the optic nerve. There are many types of glaucoma out of which two of them draw the attention which are namely open-angle glaucoma and angle-closure glaucoma. Initially, glaucoma shows no clear symptoms. Later on, the disease progresses that the eye vision becomes obscure. Thereby, glaucoma should be diagnosed early so as to prevent the loss of eye vision. If the manual examination of the eye images is done, it will be time consuming as well as correctness will depend on the proficiency of the experts. A vibrant tool nowadays is automatic detection of glaucoma which helps in preventing and detecting the most dangerous eye disease, glaucoma. For clear examination, the fundus images are collected from the fundus camera. The methodologies which are reviewed in this paper have certain benefits and flaws. With the help of this study, it will be easy to determine the best methodology for detecting glaucoma automatically.
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Shahistha, Vaidehi, K., Srilatha, J. (2020). A Review on Automatic Glaucoma Detection in Retinal Fundus Images. In: Raju, K.S., Senkerik, R., Lanka, S.P., Rajagopal, V. (eds) Data Engineering and Communication Technology. Advances in Intelligent Systems and Computing, vol 1079. Springer, Singapore. https://doi.org/10.1007/978-981-15-1097-7_41
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DOI: https://doi.org/10.1007/978-981-15-1097-7_41
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