International Journal of Image, Graphics and Signal Processing(IJIGSP)
ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)
Published By: MECS Press
IJIGSP Vol.5, No.7, Jun. 2013
Retinal Blood Vessel Segmentation with Optic Disc Pixels Exclusion
Full Text (PDF, 551KB), PP.26-33
The morphological changes of retinal blood vessels are important indicators used to diagnose and monitor the progression of various diseases. A number of retinal blood vessel segmentation methods have been introduced, including the line operator based methods, which have shown satisfactory results. However, the basic line operator method cannot discriminate the pixels around the retinal optic disc, resulting in false classification of those pixels. In this paper, we integrate the detection of pixels around the retinal optic disc to the line operator method so that those pixels can be excluded from the vessel pixels. The method is evaluated on the widely used retinal dataset, the DRIVE dataset. The results demonstrate that the proposed method has made improvements over the basic and the multi-scale line detector with accuracy and area under curve of 0.942 and 0.9521, respectively.
Cite This Paper
Randy Cahya Wihandika,Nanik Suciati,"Retinal Blood Vessel Segmentation with Optic Disc Pixels Exclusion", IJIGSP, vol.5, no.7, pp.26-33, 2013.DOI: 10.5815/ijigsp.2013.07.04
M.D. Saleh, C. Eswaran, A. Mueen, "An automated blood vessel segmentation algorithm using histogram equalization and automatic threshold selection", Journal of Digital Imaging, Vol. 24, No. 4, Aug. 2011.
A.M. Mendonça, A. Campilho, "Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction", IEEE Transactions on Medical Imaging, Vol. 25, No. 9, Sep. 2006.
U.T.V. Nguyen, A. Bhuiyan, L.A.F. Park, K. Ramamohanarao, "An effective retinal blood vessel segmentation method using multi-scale line detection", Pattern Recognition, Vol. 46, No. 3, pp. 703–715, Mar. 2013.
J. Staal, M.D. Abràmoff, M. Niemeijer, M.A. Viergever, "Ridge-based vessel segmentation in color images of the retina", IEEE Transactions on Medical Imaging, Vol. 23, No. 4, pp. 501-509, Apr. 2004.
R. Zwiggelaar, S. M. Astley, C. R. M. Boggis, and C. J. Taylor, "Linear structures in mammographic images: Detection and classiﬁcation", IEEE Transactions on Medical Imaging, Vol. 23, No. 9, pp. 1077–1086, Sep. 2004.
E. Ricci, R. Perfetti, "Retinal blood vessel segmentation using line operators and support vector machine", IEEE Transaction on Medical Imaging, Vol. 26, No. 10, pp. 1357-1365, 2007.
D. Welfer, J. Scharsanski, D.R. Marinho, "Fovea center detection based on the retina anatomy and mathematical morphology", Computer Methods and Programs in Biomedicine, Vol. 104, No. 3, Dec. 2011.
M. Niemeijer, M.D. Abràmoff, B.v. Ginneken, "Fast detection of the optic disc and fovea in color fundus photographs", Medical Image Analysis, Vol. 13, No. 6, pp. 859-870, Dec. 2009.
H.K. Hsiao, C.C. Liu, C.Y. Yu, S.W. Kuo, S.S. Yu, "A novel optic disc detection scheme on retinal images", Expert Systems with Applications, Vol. 39, No. 12, pp. 10600-10606, Sep. 2012.
H. Tjandrasa, A. Wijayanti, N. Suciati, "Optic nerve head segmentation using Hough transform and active contours", Telkomnika, Vol. 10, No. 3, pp. 531-536, Jul. 2012.
J. Xu, O. Chutatape, E. Sung, C. Zheng, P.C.T. Kuan, "Optic disk feature extraction via modiﬁed deformable model technique for glaucoma analysis", Pattern Recognition, Vol. 40, No. 7, pp. 2063-2076, Jul. 2007.
J. Kaur, H.P. Sinha, "Automated Localisation of Optic Disc and Macula from Fundus Images", International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 2, No. 4, pp. 242-249, Apr. 2012.
M. Niemeijer, J. Staal, B. van Ginneken, M. Loog, and M. D. Abramoff, "Comparative study of retinal vessel segmentation methods on a new publicly available database," in SPIE Medical Imaging, J. M. Fitzpatrick and M. Sonka, Eds., Vol. 5370, pp. 648–656, 2004.
B.S.Y. Lam, Y. Gao, A.W.C. Liew, "General retinal vessel segmentation using regularization-based multiconcavity modeling", IEEE Transactions on Medical Imaging, Vol. 29, No. 7, pp. 1369–1381, Jul. 2010.