A Snake for Retinal Vessel Segmentation

  • L. Espona
  • M. J. Carreira
  • M. Ortega
  • M. G. Penedo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4478)


This paper presents an innovative methodology to detect the vessel tree in retinal angiographies. The automatic analysis of retinal vessel tree facilitates the computation of the arteriovenous index, which is essential for the diagnosis of a wide range of eye diseases. We have developed a system inspired in the classical snake but incorporating domain specific knowledge, such as blood vessels topological properties. It profites mainly from the automatic localization of the optic disc and from the extraction and enhancement of the vascular tree centerlines. Encouraging results in the detection of arteriovenous structures are efficiently achieved, as shown by the systems performance evaluation on the publicy available DRIVE database.


Vessel Segmentation Vessel Tree Snake Model Vessel Width Thin Vessel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Niemeijer, M., van Ginneken, B., Staal, J., Suttorp-Schulten, M.S.A., Abràmoff, M.D.: Automatic Detection of Red Lesions in Digital Color Fundus Photographs. IEEE Transactions on Medical Imaging 24(5), 584–592 (2005)CrossRefGoogle Scholar
  2. 2.
    Aurell, E., et al.: A note of signs in the fundus oculi and arterial hypertension conventional assessment and significance. Bull. World Health Organ. 34, 955–960 (1967)Google Scholar
  3. 3.
    Mendoça, 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
  4. 4.
    Soares, J.V.B., Leandro, J.J.G., Cesar Jr., R.M.C., 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
  5. 5.
    Niemeijer, M., Staal, J., van Ginneken, B., Loog, M., Abràmoff, M.D.: Comparative Study of Retinal Vessel Segmentation Methods on a new Publicy Avaliable Database. In: Proceedings of the SPIE. Medical Imaging 2004: Image Processing, vol. 5370, pp. 648–656 (2004)Google Scholar
  6. 6.
    Toledo, R., Orriols, X., Binefa, X., Redeva, P., Vitri, J., Villanueva, J.J.: Tracking elongated structures using statistical snakes. In: Proceedings IEEE Conference on Computer Vision and Pattern Recognition, vol. 1(1), pp. 157–162 (2000)Google Scholar
  7. 7.
    Caderno, I.G., Penedo, M.G., Mariño, C., Carreira, M.J., Gomez-Ulla, F., González, F.: Automatic Extraction of the Retina AV Index. In: Campilho, A.C., Kamel, M. (eds.) ICIAR 2004. LNCS, vol. 3212, pp. 132–140. Springer, Heidelberg (2004)Google Scholar
  8. 8.
    Ortega, M., Mariño, C., Penedo, M.G., Blanco, M., González, F.: Personal Authentication based on Feature Extraction and Optic Nerve Location in Digital Retinal Images. Wseas Transactions on Computers 5(6), 1169–1176 (2006)Google Scholar
  9. 9.
    Kass, M., Witkin, A., Terzopoulos, D.: Active Contour Models. International Journal of Computer Vision 1(2), 321–331 (1998)Google Scholar
  10. 10.
    Canny, J.A.: Computational Approach to Edge-Detection. IEEE Transactions on Pattern Analysis and Machine Inteligence 8(6), 679–689 (1986)CrossRefGoogle Scholar
  11. 11.
    Blanco, M., Penedo, M.G., Barreira, N., Penas, M., Carreira, M.J.: Localization and Extraction of the Optic Disc Using the Fuzzy Circular Hough Transform. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds.) ICAISC 2006. LNCS (LNAI), vol. 4029, pp. 712–721. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  12. 12.
    Staal, J.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, 501–509 (2004)CrossRefGoogle Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • L. Espona
    • 1
  • M. J. Carreira
    • 1
  • M. Ortega
    • 2
  • M. G. Penedo
    • 2
  1. 1.Computer Vision Group. Dpto. Electrónica e Computación. Universidade de, Santiago de CompostelaSpain
  2. 2.Grupo VARPA. Dpto. de Computación. Universidade da CoruñaSpain

Personalised recommendations