Phase congruency based retinal vessel segmentation

Detection of blood vessels in a retinal fundus image is the preliminary step to diagnose several retinal diseases. There exist a number of methods to accomplish this task automatically. However, all of these methods suffer from lengthy processing time. The other major use of retina scanning is biome...

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Bibliographic Details
Published in2009 International Conference on Machine Learning and Cybernetics Vol. 4; pp. 2458 - 2462
Main Authors Amin, M.A., Hong Yan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2009
Subjects
Authentication
Biomedical imaging
Biometrics
Blood vessels
Blood-vessel detection
Diseases
fundus image
Image segmentation
Log-Gabor wavelets
phase congruency
Real time systems
Retina
Retinal vessels
Testing
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Summary:Detection of blood vessels in a retinal fundus image is the preliminary step to diagnose several retinal diseases. There exist a number of methods to accomplish this task automatically. However, all of these methods suffer from lengthy processing time. The other major use of retina scanning is biometric authentication, for which a real time vessel detection system is required. In this work we describe a method that acquires binary vessel image from a color retinal fundus image in near real time. This method first generates the phase congruency image of the green channel of a color retinal image, and then thresholding is applied on the phase congruency image to obtain the blood vessels. Our method is able to acquire the blood vessels from a retinal fundus image within 10 seconds on a PC with the values of dasiaaccuracypsila and dasiaarea under ROCpsila: (0.92, 0.94) for the standard testing database called DRIVE. However, a (0.90, 0.91) accuracy and area under ROC can be acquired in less than 2 sec.
ISBN:9781424437023
1424437024
ISSN:2160-133X
DOI:10.1109/ICMLC.2009.5212201