Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1977
Title: A mobile base application for cataract and conjunctivitis detection
Authors: Soysa, A
De Silva, D. I
Keywords: Cataract
Conjunctivitis
Image Processing
CNN
Keras
TensorFlow
Issue Date: 2020
Publisher: University of Kelaniya
Series/Report no.: Proceedings of ICACT;Pages 76-78
Abstract: With time the life patterns of humans have evolved at a rapid space. Today, it has come to a point where people are opting to put their health status behind other priorities in life. A contemporary example is the spreading of the COVID-19 virus. One of the other significant health issues faced by the present-day community is illnesses related to the eyes. However, unlike other health issues, most of the eye diseases can be cured with proper attention. Cataract and Conjunctivitis are identified as two of the main eye diseases faced by a mass amount of people around the world. If left untreated, these diseases can even lead to blindness. As a matter of fact, Cataract has been reported as the first cause of blindness by the world health organization. Typically, the detection of these diseases is done by an ophthalmologist with the use of a special medical equipment. Thus, the channeling of an ophthalmologist has become a mandatory requirement for the detection of these diseases. In addition, the availability of medical equipment and medical officers is deficient in rural areas. Thus, as a solution for the above-mentioned issues, it was decided to propose a mobilebased application, Eye Plus, for the detection of Cataract and Conjunctivitis diseases. Using Eye Plus, one would be able to test his/her eyes at a convenient time in any place for a zero cost. In addition, it provides additional information related to Cataract and Conjunctivitis diseases. Another special feature of the application is the ability to operate it without the help of another party. At present, the application achieved a success rate of 83.3% for a collection of 150 images.
URI: http://rda.sliit.lk/handle/123456789/1977
Appears in Collections:Research Papers - Open Access Research
Research Papers - SLIIT Staff Publications
Research Publications -Dept of Information Technology

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