Paper Info
Title
Optic disc detection in color fundus images using ant colony optimization.
Abstract
Diabetic retinopathy has been revealed as the most common cause of blindness among people of working age in developed countries. However, loss of vision could be prevented by an early detection of the disease and, therefore, by a regular screening program to detect retinopathy. Due to its characteristics, the digital color fundus photographs have been the easiest way to analyze the eye fundus. An important prerequisite for automation is the segmentation of the main anatomical features in the image, particularly the optic disc. Currently, there are many works reported in the literature with the purpose of detecting and segmenting this anatomical structure. Though, none of them performs as needed, especially when dealing with images presenting pathologies and a great variability. Ant colony optimization (ACO) is an optimization algorithm inspired by the foraging behavior of some ant species that has been applied in image processing with different purposes. In this paper, this algorithm preceded by anisotropic diffusion is used for optic disc detection in color fundus images. Experimental results demonstrate the good performance of the proposed approach as the optic disc was detected in most of all the images used, even in the images with great variability.
Year
DOI
Venue
2013
10.1007/s11517-012-0994-5
Med. Biol. Engineering and Computing
Keywords
Field
DocType
Anisotropic diffusion, Ant colony optimization, Diabetic retinopathy, Digital color fundus image, Medical image processing
Ant colony optimization algorithms,Anisotropic diffusion,Retinopathy,Computer vision,Segmentation,Fundus (eye),Image processing,Optic disc,Artificial intelligence,Optimization algorithm,Mathematics
Journal
Volume
Issue
ISSN
51
3
1741-0444
Citations 
PageRank 
References 
16
0.63
20
Authors
3
Name
Order
Citations
PageRank
Carla Pereira1403.74
Luís Gonçalves2456.19
Manuel Ferreira3637.20