An Effective Supervised Framework for Retinal Blood Vessel Segmentation Using Local Standardisation and Bagging

  • Uyen T. V. Nguyen
  • Alauddin Bhuiyan
  • Kotagiri Ramamohanarao
  • Laurence A. F. Park
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7009)


In this paper, we present a supervised framework for extracting blood vessels from retinal images. The local standardisation of the green channel of the retinal image and the Gabor filter responses at four different scales are used as features for pixel classification. The Bayesian classifier is used with a bagging framework to classify each image pixel as vessel or background. A post processing method is also proposed to correct central reflex artifacts and improve the segmentation accuracy. On the public DRIVE database, our method achieves an accuracy of 0.9491 which is higher than any existing methods. More importantly, visual inspection on the segmentation results shows that our method gives two important improvements on the segmentation quality: vessels are well separated and central reflex are effectively removed. These are important factors that affect to the accuracy of all subsequent vascular analysis.


Retinal images blood vessel segmentation central reflex Gabor filter Bayeisan classifier bagging 


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  1. 1.
    Wong, T.Y., Klein, R., Sharrett, A.R., Duncan, B.B., Couper, D.J., Tielsch, J.M., Klein, B.E.K., Hubbard, L.D.: Retinal arteriolar narrowing and risk of coronary heart disease in men and women: the atherosclerosis risk in communities study. Jama 287(9), 1153 (2002)CrossRefGoogle Scholar
  2. 2.
    Chaudhuri, S., Chatterjee, S., Katz, N., Nelson, M., Goldbaum, M.: Detection of blood vessels in retinal images using two-dimensional matched filters. IEEE Transactions on Medical Imaging 8(3), 263–269 (2002)CrossRefGoogle Scholar
  3. 3.
    Hoover, A., Kouznetsova, V., Goldbaum, M.: Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response. IEEE Transactions on Medical Imaging 19(3), 203–210 (2002)CrossRefGoogle Scholar
  4. 4.
    Liu, I., Sun, Y.: Recursive tracking of vascular networks in angiograms based on the detection-deletion scheme. IEEE Transactions on Medical Imaging 12(2), 334–341 (2002)CrossRefGoogle Scholar
  5. 5.
    Jiang, X., Mojon, D.: Adaptive local thresholding by verification-based multithreshold probing with application to vessel detection in retinal images. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(1), 131–137 (2003)CrossRefGoogle Scholar
  6. 6.
    Mendonca, A.M., Campilho, A.: Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction. IEEE Transactions on Medical Imaging 25(9), 1200–1213 (2006)CrossRefGoogle Scholar
  7. 7.
    Lam, B.S.Y., Gao, Y., Liew, A.W.C.: General retinal vessel segmentation using regularization-based multiconcavity modeling. IEEE Transactions on Medical Imaging 29(7), 1369–1381 (2010)CrossRefGoogle Scholar
  8. 8.
    Staal, J., Abràmoff, M.D., Niemeijer, M., Viergever, M.A., van Ginneken, B.: Ridge-based vessel segmentation in color images of the retina. IEEE Transactions on Medical Imaging 23(4), 501–509 (2004)CrossRefGoogle Scholar
  9. 9.
    Soares, J.V.B., Leandro, J.J.G., Cesar, R., Jelinek, H.F., Cree, M.J.: Retinal vessel segmentation using the 2-d gabor wavelet and supervised classification. IEEE Transactions on Medical Imaging 25(9), 1214–1222 (2006)CrossRefGoogle Scholar
  10. 10.
    Marín, D., Aquino, A., Gegúndez, M., Bravo, J.: A new supervised method for blood vessel segmentation in retinal images by using gray-level and moment invariants-based features. IEEE Transactions on Medical Imaging (2010)Google Scholar
  11. 11.
    Movellan, J.R.: Tutorial on gabor filters. Open Source Document (2002)Google Scholar
  12. 12.
    Breiman, L.: Bagging predictors. Machine Learning 24(2), 123–140 (1996)zbMATHGoogle Scholar
  13. 13.
    Niemeijer, M., Staal, J., van Ginneken, B., Loog, M., Abramoff, M.D.: Comparative study of retinal vessel segmentation methods on a new publicly available database. In: Proceedings of SPIE, vol. 5370, p. 648 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Uyen T. V. Nguyen
    • 1
  • Alauddin Bhuiyan
    • 1
  • Kotagiri Ramamohanarao
    • 1
  • Laurence A. F. Park
    • 2
  1. 1.Department of Computer Science and Software EngineeringThe University of MelbourneAustralia
  2. 2.School of Computing and MathematicsUniversity of Western SydneyAustralia

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