An Economic System for Screening of Diabetic Retinopathy Using Fundus Images
- 1 ECE, St. Joseph’s Institute of Technology, India
- 2 B.S. Abdur Rahman University, India
Abstract
Delayed length of time of the diabetes may influence the tiny blood vessels of the retina bringing about Diabetic Retinopathy (DR). It is one of the major root causes of the blindness across the globe. Routine eye screening of patients with diabetes serves to discover DR at the early stage. The conventional visual assessment protocol is time consuming and laborious. Hence, the computer aided system for DR detection can reduce the burden of the ophthalmologist and improve the accuracy. In this work, we have proposed an automatic method for screening exudates based on image processing methods which utilized color component, morphology and intensity in retinal digital fundus images. The retinal fundus image of the affected eye was recorded with a fundus camera (Visupac, CARL-ZEISS FF 450 plus) for 60 south Indian women. For each image the ground truth result was collected from two glaucoma experts with more than 10 years of experience. Then the quantitative evaluation of the proposed algorithm has been carried out using these ground truth results. We achieved the highest segmentation accuracy of 93%, F-score of 88.2%, precession and recall of 93.1 and 89.3% respectively when the ground truth results were considered as standard. The extracted morphological parameters exhibited significant differences between normal and DR groups at p<0.001, whereas, the age and BMI values depicted no such significance. In conclusion, our findings suggest that the proposed system would be a useful for mass screening of DR.
DOI: https://doi.org/10.3844/ojbsci.2014.254.260
Copyright: © 2014 G.S. Annie Grace Vimala and S. Kaja Mohideen. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Fundus Image
- Diabetic Retinopathy
- Image Processing
- Mathematical Morphology
- Statistical Analysis