Grading System for Diabetic Retinopathy Disease
N. D. Salih, Marwan D. Saleh, C. Eswaran, and Junaidi Abdullah
Centre for Visual Computing, Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor, Malaysia
Abstract—Diabetic Retinopathy (DR) has become a serious threat to our society causing 45% of the legal blindness in diabetes patients. Early detection as well as the periodic screening of DR helps in reducing the progress of this disease and in preventing the subsequent loss of visual capability. This paper presents an automated grading system for DR based on fundus images. The severity level of DR is classified using features such as microaneurysms (MAs) and hemorrhages (HAs) which are extracted from the fundus images. Based on the experimental results, it is found that the developed system yields remarkable and promising results even though only low-quality images have been used as test images.
Index Terms—diabetic retinopathy, contrast enhancement, H-maxima transform, multilevel thresholding, mathematical morphology
Cite: N. D. Salih, Marwan D. Saleh, C. Eswaran, and Junaidi Abdullah, "Grading System for Diabetic Retinopathy Disease," International Journal of Signal Processing Systems, Vol. 5, No. 1, pp. 34-38, March 2017. doi: 10.18178/ijsps.5.1.34-38
Cite: N. D. Salih, Marwan D. Saleh, C. Eswaran, and Junaidi Abdullah, "Grading System for Diabetic Retinopathy Disease," International Journal of Signal Processing Systems, Vol. 5, No. 1, pp. 34-38, March 2017. doi: 10.18178/ijsps.5.1.34-38