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dc.contributor.authorBhardwaj, Charu-
dc.contributor.authorJain, Shruti-
dc.contributor.authorSood, Meenakshi-
dc.descriptionIndonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol. 7, No. 4, Dec 2019, pp. 757~771 ISSN: 2089-3272, DOI: 10.11591/ijeei.v7i4.991en_US
dc.description.abstractDiabetic Retinopathy is a retinal vascular disease that is characterized by progressive deterioration of blood vessels in the retina and is distinguished by the appearance of different types of clinical lesions like microaneurysms, hemorrhages, exudates etc. Automated detection of the lesions plays significant role for early diagnosis by enabling medication for the treatment of severe eye diseases preventing visual loss. Extraction of blood vessels can facilitate ophthalmic services by automating computer aided screening of fundus images. This paper presents blood vessel extraction algorithms with ensemble of pre-processing and post-processing steps which enhance the image quality for better analysis of retinal images for automated detection. Extensive performance-based evaluation of the proposed approaches is done over four databases on the basis of statistical parameters. Comparison of both blood vessel extraction techniques on different databases reveals that fuzzy based approach gives better results as compared to Kirsch’s based algorithm. The results obtained from this study reveal that 89% average accuracy is offered by the proposed MBVEKA and 98% for proposed BVEFA.en_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectBlood Vessel Extractionen_US
dc.subjectDiabetic Retinopathyen_US
dc.subjectKirsch’s Algorithm.en_US
dc.titleAutomatic Blood Vessel Extraction of Fundus Images Employing Fuzzy Approachen_US
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