Detection of blood vessels in ophthalmoscope images using MF/ant (matched filter/ant colony) algorithm

• Published in: Computer methods and programs in biomedicine Vol. 96; no. 2; pp. 85 - 95
• Main Authors: Cinsdikici, Muhammed Gökhan, Aydın, Doğan
• Format: Journal Article
• Language: English
• Published: Ireland Elsevier Ireland Ltd 01.11.2009
• Subjects: Algorithms; Ant algorithm; Artificial Intelligence; DRIVE database; Formicidae; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Internal Medicine; Matched filter; Ophthalmoscopy - methods; Other; Pattern Recognition, Automated - methods; Reproducibility of Results; Retinal (Ophthalmoscope) image blood vessel segmentation; Retinal Vessels - anatomy & histology; Retinal Vessels - cytology; Sensitivity and Specificity; Subtraction Technique; DRIVE database; Matched filter; Retinal (Ophthalmoscope) image blood vessel segmentation; Ant algorithm
• ISSN: 0169-2607; 1872-7565
• DOI: 10.1016/j.cmpb.2009.04.005

Abstract Blood vessels in ophthalmoscope images play an important role in diagnosis of some serious pathologies on retinal images. Hence, accurate extraction of vessels is becoming a main topic of this research area. Matched filter (MF) implementation for blood vessel detection is one of the methods giving more accurate results. Using this filter alone might not recover all the vessels (especially the capillaries). In this paper, a novel approach (MF/ant algorithm) is proposed to overcome the deficiency of the MF. The proposed method is a hybrid model of matched filter and ant colony algorithm. In this work, the accuracy and parameters of the hybrid algorithm are also discussed. The proposed method shows its success using the well known reference ophthalmoscope images of DRIVE database.