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.

A new approach to optic disc detection in human retinal images using the firefly algorithm

“…The results achieved by the application of the proposed method to the STARE and DiaRetDB1 datasets are as good as or better than those described in previous works [10,20,21,24,28]. Due to the importance of using real images, we intend to develop an authoritative system and clinical applications.…”

“…The algorithm proposed in [20] is based on ant colony optimization (ACO) and uses an anisotropic diffusion process that aims to smooth the retinal blood vessels. The ACO algorithm can detect the optic disc edges.…”

Quality evaluation of digital fundus images through combined measures

“…This latter mask is obtained by detecting the optic disc position using the method described in Ref. 22, and defining a rectangular region approximately macula centered. The optic disc coordinates allow us to know if the fundus image is left/right or centered in the optic disc to then adequately define the mask position.…”

Exudate segmentation in fundus images using an ant colony optimization approach

“…E-mail address: id2723@alunos.uminho.pt (C. Pereira). Information Sciences 296 (2015) [14][15][16][17][18][19][20][21][22][23][24] Contents lists available at ScienceDirect Information Sciences j o u r n a l h o m e p a g e : w w w . e l s e v i e r .…”

“…The ACO algorithm has been used in digital image processing with different purposes such as edge detection [27,31], image segmentation [13,17,26], visual saliency detection [16], and image thresholding [19]. ACO has been used in fundus images to locate the OD [14,22] and segment retinal blood vessels [4,11]. However, this type of approach has never been applied to retinal images to detect DR lesions.…”