TY - GEN
T1 - Phase congruency based retinal vessel segmentation
AU - Amin, M.Ashraful
AU - Yan, Hong
PY - 2009
Y1 - 2009
N2 - 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 'accuracy' and 'area under ROC: (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. © 2009 IEEE.
AB - 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 'accuracy' and 'area under ROC: (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. © 2009 IEEE.
KW - Blood-vessel detection
KW - Fundus image
KW - Log-Gabor wavelets
KW - Phase congruency
KW - Retina
UR - https://www.scopus.com/pages/publications/70350736249
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-70350736249&origin=recordpage
U2 - 10.1109/ICMLC.2009.5212201
DO - 10.1109/ICMLC.2009.5212201
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781424437030
VL - 4
SP - 2458
EP - 2462
BT - Proceedings of the 2009 International Conference on Machine Learning and Cybernetics
T2 - 2009 International Conference on Machine Learning and Cybernetics
Y2 - 12 July 2009 through 15 July 2009
ER -