Classification of Diabetic Retinopathy Severity Levels of Transformed images using K-means and Thresholding method
Manjusha Nair1, Dhirendra Mishra2
1Manjusha Nair, Master of Technology Student, Department of Computer Engineering, NMIMS University, Mumbai (M.H), India.
2Dhirendra Mishra, Professor, UG and PG Engineering, Mumbai University, India. NMIMS university, Mumbai (M.H), India.
Manuscript received on 18 April 2019 | Revised Manuscript received on 25 April 2019 | Manuscript published on 30 April 2019 | PP: 51-61 | Volume-8 Issue-4, April 2019 | Retrieval Number: D6331048419/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Diabetic Retinopathy is one of the major eye complications which occurs because of diabetes. The main reason behind this disease is damage to the blood vessels and due to which lack of oxygen supply in retina. This paper is an extension work of the previously done This paper categorizes the severity levels of diabetic retinopathy by using clustering approach and thresholding method. Two approaches are implemented in this paper Spatial Domain and Frequency Domain for calculating Feature Vectors. Clustering is applied to these Feature Vectors and classification is done by using thresholding method. The classification with encouraging results is obtained i.e. Sensitivity, Specificity and Accuracy is 94%, 100% and 97% respectively.
Keywords: Clustering, Diabetic Retinopathy, Frequency Domain, Spatial Domain, Thresholding.
Scope of the Article: Classification