Title :
Blood vessel segmentation in retinal images based on the nonsubsampled contourlet transform
Author :
Chien-Cheng Lee ; Shih-Che Ku
Author_Institution :
Dept. of Commun. Eng., Yuan Ze Univ., Taoyuan, Taiwan
Abstract :
This paper presents a method for blood vessel segmentation in retinal images based on the nonsubsampled contourlet transform (NSCT). The method uses a line detector and different directions of the NSCT subbands to detect the direction of blood vessel for each NSCT level. Then, the method computes three kinds of features using the orthogonal direction of blood vessel of the NSCT coefficients. After pixel classification, we present three kinds of post-processing procedures to correct the optic disk, the field of view mask, lesion areas, and noise. The performance is evaluated on the DRIVE database. The average accuracy of the DRIVE databases evaluation is 0.9423.
Keywords :
blood vessels; eye; feature extraction; image classification; image resolution; image segmentation; medical image processing; object detection; transforms; DRIVE database; NSCT coefficients; NSCT level; blood circulation system diagnosis; blood vessel direction detection; blood vessel segmentation method; lesion areas correction; line detector; noise correction; nonsubsampled contourlet transform; optic disk correction; pixel classification; retinal images; retinal imaging diagnosis; view mask correction; Adaptive optics; Biomedical imaging; Blood vessels; Feature extraction; Image segmentation; Optical imaging; Retina; blood vessel; nonsubsampled contourlet transform; retinal image;
Conference_Titel :
Information Security and Intelligence Control (ISIC), 2012 International Conference on
Conference_Location :
Yunlin
Print_ISBN :
978-1-4673-2587-5
DOI :
10.1109/ISIC.2012.6449775
