Programs
- M. Tech. in Automotive Engineering -
- B. Sc. Clinical Nutrition, Dietetics, and Food Science - Undergraduate
Publication Type : Journal Article
Publisher : Journal of Digital Imaging
Source : Journal of Digital Imaging, Volume 23, Number 4, p.430-437 (2010)
Keywords : algorithm, Algorithms, aneurysm, article, Automated, automated pattern recognition, Automatic Detection, computer assisted diagnosis, Computer-Assisted, Diabetic Retinopathy, diagnostic imaging, Digital fundus images, Experimental evaluation, eye fundus, Fundus, Fundus Oculi, Hemorrhages, human, Humans, Image Enhancement, Image Interpretation, Matched filters, Mathematical morphology, methodology, Microaneurysms, Morphology, Ocular fundus images, Pattern recognition, Photography, Pixel classification, radiography, Red lesions, Retina, retina blood vessel, retina hemorrhage, Retinal Hemorrhage, Retinal Vessels, Signal processing
Year : 2010
Abstract : An efficient approach for automatic detection of red lesions in ocular fundus images based on pixel classification and mathematical morphology is proposed. Experimental evaluation of the proposed approach demonstrates better performance over other red lesion detection algorithms, and when determining whether an image contains red lesions the proposed approach achieves a sensitivity of 100% and specificity of 91%. Copyright © 2010 by Society for Imaging Informatics in Medicine.
Cite this Research Publication : G. Ba Kande, Savithri, T. Sb, and Subbaiah, P. Vc, “Automatic detection of microaneurysms and hemorrhages in digital fundus images”, Journal of Digital Imaging, vol. 23, pp. 430-437, 2010.