Feature Extraction to Detect Diabetic Retinopathy and Glaucoma in Fundus Image
DOI:
https://doi.org/10.37591/rrjomst.v7i1.117Abstract
Visual impairment due to various eye-related diseases can be largely prevented through regular fundus colour image screening. Large scale screening of the retinal image in the early stages is crucial to disease diagnosis. It is reported that the number of ophthalmologist ratios is very low. Hence, the computer-aided screening is required where the diagnosis of disease from an image is done from the main features of the fundus image. In this work, an attempt has been made to design an algorithm to extract two features, viz. ISNT ratio and micro-aneurysm which individually signifies glaucoma and diabetic retinopathy respectively. The proposed features extraction method is clinically significant and can be utilized to distinguish glaucoma and diabetic retinopathy precisely.
Keywords: Fundus image, ISNT ratio, micro-aneurysm, glaucoma, diabetic retinopathy
Cite this Article
Himanshu Kumar, Rakhi Agarwal, Shatakshi Singh. Feature Extraction to Detect Diabetic Retinopathy and Glaucoma in Fundus Image. Research & Reviews: Journal of Medical Science and Technology. 2018; 7(1): 9–12p.
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