Title :
eOphthalmologist -- Intelligent Eye Disease Diagnosis System
Author :
Manoujitha Kugamourthy;Oshini Goonetileke
Author_Institution :
Dept. of Comput., Inf. Inst. of Technol. in affiliation with Univ. of Westminster, Colombo, Sri Lanka
Abstract :
The human eye is a vital organ of vision which can be affected by many diseases. One of the most common diseases that have affected people of over 50 years of age is Age Related Macular Degeneration. Patients in their fifties or more or who have undergone surgery for cataract and glaucoma should have their eyes examined annually. Inspection provides a large number of Fundus images and medical professionals has to continually peruse them spending valuable time and energy. Current methods of detection and assessment are manual, expensive and potentially inconsistent. Thus, it would be more cost effective and beneficial if the initial task of analysing retinal photographs is automated. The proposed solution would act as an early warning system, where an ophthalmologist will be able to analyse numerous images within a brief period and spend more time on those patients who are actually in desideratum of their expertise.
Keywords :
"Image edge detection","Optical imaging","Optical filters","Image segmentation","Retina","Diseases","Lesions"
Conference_Titel :
Intelligent Systems, Modelling and Simulation (ISMS), 2014 5th International Conference on
DOI :
10.1109/ISMS.2014.64