J Med Syst - An integrated index for the identification of diabetic retinopathy stages using texture parameters.

Tópicos

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Resumo

Diabetes is a condition of increase in the blood sugar level higher than the normal range. Prolonged diabetes damages the small blood vessels in the retina resulting in diabetic retinopathy (DR). DR progresses with time without any noticeable symptoms until the damage has occurred. Hence, it is very beneficial to have the regular cost effective eye screening for the diabetes subjects. This paper documents a system that can be used for automatic mass screenings of diabetic retinopathy. Four classes are identified: normal retina, non-proliferative diabetic retinopathy (NPDR), proliferative diabetic retinopathy (PDR), and macular edema (ME). We used 238 retinal fundus images in our analysis. Five different texture features such as homogeneity, correlation, short run emphasis, long run emphasis, and run percentage were extracted from the digital fundus images. These features were fed into a support vector machine classifier (SVM) for automatic classification. SVM classifier of different kernel functions (linear, radial basis function, polynomial of order 1, 2, and 3) was studied. Receiver operation characteristics (ROC) curves were plotted to select the best classifier. Our proposed system is able to identify the unknown class with an accuracy of 85.2%, and sensitivity, specificity, and area under curve (AUC) of 98.9%, 89.5%, and 0.972 respectively using SVM classifier with polynomial kernel of order 3. We have also proposed a new integrated DR index (IDRI) using different features, which is able to identify the different classes with 100% accuracy.

Resumo Limpo

diabet condit increas blood sugar level higher normal rang prolong diabet damag small blood vessel retina result diabet retinopathi dr dr progress time without notic symptom damag occur henc benefici regular cost effect eye screen diabet subject paper document system can use automat mass screen diabet retinopathi four class identifi normal retina nonprolif diabet retinopathi npdr prolif diabet retinopathi pdr macular edema use retin fundus imag analysi five differ textur featur homogen correl short run emphasi long run emphasi run percentag extract digit fundus imag featur fed support vector machin classifi svm automat classif svm classifi differ kernel function linear radial basi function polynomi order studi receiv oper characterist roc curv plot select best classifi propos system abl identifi unknown class accuraci sensit specif area curv auc respect use svm classifi polynomi kernel order also propos new integr dr index idri use differ featur abl identifi differ class accuraci

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