A Review Paper On Detection And Extraction Of Blood Vessels, Microaneurysms And Exudates From Fundus Images
Soju George, Bhailal Limbasiya
Index Terms: Blood vessels, BPDFHE, CLAHE, Diabetic retinopathy, Exudates, Fundus, Microaneurysms.
Abstract: Diabetic Retinopathy (DR) is a medical condition which affects the normal vision of a human. Patients having long history of diabetes tend to be affected by DR. An increased level of blood sugar may lead to an eye disease termed as DR. Early detection of DR helps the ophthalmologists to advise proper treatment to save the vision of the patient. In this paper, a survey has been carried out and different techniques are discussed to extract different features. Exudates, Microaneurysms and abnormal growth of blood vessels are some of the symptoms of DR. Preprocessing of an image is always required to obtain a contrast enhanced image. The paper provides overview of some of the preprocessing techniques used till now and different methods to extract exudates, microaneurysms and blood vessels are discussed.
 G. Rajput, Preethi N. Patil and Ramesh Chavan, “Automatic detection of microaneurysms from fundus images using morphological operations”, Lecture Notes in Electrical Engineering/Springer India 2013.
 Rupsa Bhattacharjee and Dr. Monisha Chakraborty, “Exudates, retinal and statistical features detection from diabetic retinopathy and normal fundus images: an automated comparative approach”, 2012 National Conference on Computing and Communication Systems (NCCCS) organized by IEEE, 978-1-4673-1953-9/12.
 Marwan D Saleh and C. Eswaran, “An automated blood vessel extraction algorithm in fundus images”, 2012 IEEE International conference on Bioinformatics and Bio-medicine,978-1-4673-2560-8/12, pg 482-486.
 T.Yamuna and S.Maheswari, “Detection of abnormalities in retinal images”, 2013 IEEE International Conference on Emerging Trends in Computing, Communication and Nanotechnology (ICECCN 2013), 978-1-4673-5036-5/13, pg 236-240.
 Paintamilselvi and Shyamala, “A novel method to detect the fovea of fundus retinal image”, 2012 International journal for research and development in engineering (IJRDE), Vol.1: Issue.1, June-July 2012 pp- 21-25
 Anitha Mohan and K. Moorthy, “Early detection of diabetic retinopathy edema using FCM”, International Journal of Science and Research (IJSR), India, May 2013. ISSN: 2319-7064.
 S. Ravishankar, A. Jain, A. Mittal, “Automated feature extraction for early detection of diabetic retinopathy in fundus images”, IEEE CVPR, pp. 210-217, 2009.
 Silvia, R.C.; Vijayalakshmi, R., “Detection of non-proliferative diabetic retinopathy in fundus images of the human retina”, Information Communication and Embedded Systems (ICICES), 2013 International Conference on , vol., no., pp.978,983, 21-22 Feb. 2013.
 V Sarvanan, b. Venkatalaksmi and vithiya rajendran, “Automated red lesion detection in diabetic retinopathy” Proceedings of 2013 IEEE Conference on Information and Communication Technologies (ICT 2013), 978-1-4673-5758-6/13, pg 236-239.
 DIARETDB0 database, http://www.it.lut.fi/project/imageret
 Gandhi, M, Dhanasekaran, R., "Diagnosis of diabetic retinopathy using morphological process and SVM classifier," Communications and Signal Processing (ICCSP), 2013 International Conference on , vol., no., pp.873,877, 3-5 April 2013.
 Tamilarasi, M.; Duraiswamy, K., "Genetic based Fuzzy Seeded Region Growing Segmentation for diabetic retinopathy images," Computer Communication and Informatics (ICCCI), 2013 International Conference on ,