Classification of Glaucoma and Bright Lesions in Retinal Fundus Images using SVM
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Date
2017-08
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G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand)
Abstract
In terms of population, India stands at the second position in the world, and with such a huge population it is very difficult to provide medical assistance to each and every one especially to those living in the remote areas. As these retinal diseases require regular check-ups and timely intervention to control the progress of disease, an ophthalmologist with all the medical equipment is required which could be highly expansive. Therefore an automated clinical support system should be developed for the diagnosis of retinal diseases like glaucoma and diabetic retinopathy which could be used to make the screening of real time population easy and efficient and also identify those who are at risk in the early stages. This technique would minimize the cost, estimation time and also assist the ophthalmologist to perform the treatment plan. This thesis presents a classification system for the diagnosis of Glaucoma and Bright Lesions in retinal fundus images where different anatomical and statistical features are extracted and classified using SVM. It has been observed that the anatomical features proved to be a promising features as compared to the other statistical features and a good accuracy is achieved using SVM classification. In this thesis work the performance analysis of this classification system over different feature sets is reported and discussed.
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