You are in:Home/Publications/Ant Colony-based System for Retinal Blood Vessels Segmentation. Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012) Advances in Intelligent Systems and Computing Volume 201, 2013, pp 441-452. DOI: 10.1007/978-81-322-1038-2_37

Dr. Assoc. Prof. Ahmad Taher Azar :: Publications:

Title:
Ant Colony-based System for Retinal Blood Vessels Segmentation. Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012) Advances in Intelligent Systems and Computing Volume 201, 2013, pp 441-452. DOI: 10.1007/978-81-322-1038-2_37
Authors: Ahmed. H. Asad, Ahmad Taher Azar, Aboul Ella Hassaanien
Year: 2012
Keywords: Not Available
Journal: Not Available
Volume: Not Available
Issue: Not Available
Pages: Not Available
Publisher: Not Available
Local/International: International
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Full paper Not Available
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Abstract:

The segmentation of retinal blood vessels in the eye funds images is crucial stage in diagnosing infection of diabetic retinopathy. Traditionally, the vascular network is mapped by hand in a time-consuming process that requires both training and skill. Automating the process allows consistency, and most im-portantly, frees up the time that a skilled technician or doctor would normally use for manual screening. Several studies were carried out on the segmentation of blood vessels in general, however only a small number of them were associated to retinal blood vessels. In this paper, an approach for segmenting retinal blood ves-sels is presented using only ant colony system. It uses eight features; four are based on gray-level and four are based on Hu moment-invariants. The features are directly computed from values of image pixels, so they take about 90 seconds in computation. The performance evaluation of this system is estimated by using classification accuracy. The presented approach accuracy is 90.28% and its sensi-tivity is 74%.

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