Disease Severity Based On Areas of Exudates, Blood Vessels and Micro-Aneurysms in Retinal Fundus Images Using K-Means Clustering
Journal Title: International Journal of Engineering and Science Invention - Year 2018, Vol 7, Issue 2
Abstract
Diabetic retinopathy (DR) is a kind of disease that attacks retina of human eye occurs mainly due to diabetes because of diabetes there is elaboration of sugar levels in body. Due to DR Patient losses his vision; earlier exposure can diminish the complication of visual detoriation. Existence of micro-aneurysms, cotton-wool spots, hemorrahages and exudates are indication of DR. Micro aneurysms and exudates are foremost signs of DR and can be blocked with a recent diagnosis. Digital fundus image collected from fundus camera helps in analyzing the exudates and micro-aneurysms in prior way. This thesis proposes a method which has two essential steps they are coarse segmentation executed by k-means clustering and fine segmentation executed by morphological image processing for disclosure of required features such as exudates, micro-aneurysms and blood vessels on retinal images of very low contrast. Initially pre-processing of retinal images are performed. Later segmentation of the processed images is done through K-Means clustering. In order to specify these segmented regions into Non-Exudates (blood vessels and micro aneurysms) and Exudates a special set of features which are based on colour and texture are derived from Morphological operations are done to acquire the perfect classification. As disclosure of exudates, and micro aneurysms existing in limited areas can easily identified using this technique hence this technique appears encouraging. Depending upon the area of exudates, blood vessels and micro aneurysms disease severity can be explained whether it is mild or in severe stage.
Authors and Affiliations
Dr. P. V. Ramaraju, I. H. S. Manisree
Keywords
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