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@article{146372,
        author = {ANJU K ABRAHAM and SANGEETA T.R},
        title = { A Robust Computer Aided System For Retinal Screening},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {12},
        pages = {365-370},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=146372},
        abstract = {Diabetic retinopathy (DR) and Diabetic Maculopathy (DM) are nowadays two of the most frequent causes of blindness and vision loss. In addition, these diseases will experience a high growth in the future due to diabetes incidence increase and ageing population in the current society. Computer aided diagnosis system is very much used for medical image screening. There are some limitations to find the fundus diseases from fundus images. This proposed work investigates discrimination capabilities in the texture, color and histogram of fundus images to differentiate between pathological and healthy images. For this purpose, Gray level co-occurrence matrix taken as a texture descriptor, in addition the color and histogram features to increase the feature strength. Initially the optical cup to disk ratio and rim to disc ratio is find out to analyze the glaucoma disease with expert results. Then the DR and DM analyzed with the help of extracted features. Then SVM classifier acting as a classifier to find the diseases. The proposed procedure obtaining promising results. Thus the proposed system well suitable for fundus image screening, compared to other conventional computer aided system methods},
        keywords = {CDR, RDR, GLCM, Color moments, Color histograms, SVM Classifier},
        month = {},
        }