Advertisement

Automatic Detection of Blood Vessels in Retinal OCT Images

  • Joaquim de MouraEmail author
  • Jorge Novo
  • José Rouco
  • M. G. Penedo
  • Marcos Ortega
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10338)

Abstract

The eye is a non-invasive window where clinicians can observe and study in vivo the retinal vasculature, allowing the early detection of different relevant pathologies. In this paper, we present a complete methodology for the automatic vascular detection in retinal OCT images. To achieve this, we analyse the intensity profiles between representative layers of the retina, layers that are previously segmented. Then, we propose the use of two threshold-based strategies for vessel detection, a fixed and an adaptive approach. Both methods have been tested and validated with 128 OCT images, that include 560 vessels that were labelled by an ophthalmologist. The approaches provided satisfactory results, facilitating the doctors’ work and allowing better analysis and treatment of vascular diseases.

Keywords

Computer-aided diagnosis Retinal imaging Optical coherence tomography Vessel detection 

Notes

Acknowledgments

This work is supported by the Instituto de Salud Carlos III of the Spanish Government and FEDER funds of the European Union through the PI14/02161 and the DTS15/00153 research projects.

References

  1. 1.
    Nguyen, T., Wong, T.Y.: Retinal vascular changes and diabetic retinopathy. Curr. Diab. Rep. 113(9), 277–283 (2009)CrossRefGoogle Scholar
  2. 2.
    Won, T.Y., Mitchell, P.: Retinal vascular changes and diabetic retinopathy. N. Engl. J. Med. 351, 2310–2317 (2004)CrossRefGoogle Scholar
  3. 3.
    Klein, R., Sharrett, A.R., Klein, B.E., Chambless, L.E., Cooper, L.S., Hubbard, L.D., Evans, G.: Are retinal arteriolar abnormalities related to atherosclerosis? The atherosclerosis risk in communities study. Arterioscler. Thromb. Vasc. Biol. 20, 1644–1650 (2000)CrossRefGoogle Scholar
  4. 4.
    Huang, D., Swanson, E., Lin, C., Schuman, J., Stinson, W., Chang, W., Hee, M., Flotte, T., Gregory, K., Puliafito, C.: Optical coherence tomography. Science 254, 1178 (1991)CrossRefGoogle Scholar
  5. 5.
    Elbalaoui, A., Fakir, M., Taifi, K., Merbouha, A.: Automatic detection of blood vessel in retinal images. In: 13th International Conference on Computer Graphics, pp. 324–332 (2016)Google Scholar
  6. 6.
    Chutatape, O., Zheng, L., Krishnan, S.: Retinal blood vessel detection and tracking by matched Gaussian and Kalman filters. In: Engineering in Medicine and Biology Society, pp. 3144–3149 (1998)Google Scholar
  7. 7.
    Nekovei, R., Sun, Y.: Back-propagation network and its configuration for blood vessel detection in angiograms. IEEE Trans. Neural Netw. 6, 64–72 (1995)CrossRefGoogle Scholar
  8. 8.
    Espona, L., Carreira, M., Penedo, M., Ortega, M.: Retinal vessel tree segmentation using a deformable contour model. IEEE Trans. Neural Netw. 1–4 (2008)Google Scholar
  9. 9.
    Niemeijer, M., Garvin, M., Ginneken, B., Sonka, M., Abramoff, M.: Vessel segmentation in 3D spectral OCT scans of the retina. In: Medical Imaging, p. 69141 (2008)Google Scholar
  10. 10.
    Guimarães, P., Rodrigues, P., Lobo, C., Leal, S., Figueira, J., Serranho, P., Bernardes, R.: Ocular fundus reference images from optical coherence tomography. Comput. Med. Imaging Graph. 38, 381–389 (2014)CrossRefGoogle Scholar
  11. 11.
    Moura, J., Novo, J., Ortega, M., Barreira, N., Penedo, M.G.: Vessel tree extraction and depth estimation with OCT images. In: Luaces, O., Gámez, J.A., Barrenechea, E., Troncoso, A., Galar, M., Quintián, H., Corchado, E. (eds.) CAEPIA 2016. LNCS, vol. 9868, pp. 23–33. Springer, Cham (2016). doi: 10.1007/978-3-319-44636-3_3 CrossRefGoogle Scholar
  12. 12.
    Ortega, M., López, A.G., Penedo, M.G., Cardeñoso, P.C.: Implementation and optimization of a method for retinal layer extraction and reconstruction in optical coherence tomography images. Med. Appl. Artif. Intell. 12, 175–191 (2013)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Joaquim de Moura
    • 1
    Email author
  • Jorge Novo
    • 1
  • José Rouco
    • 1
  • M. G. Penedo
    • 1
  • Marcos Ortega
    • 1
  1. 1.Department of ComputingUniversity of A CoruñaA CoruñaSpain

Personalised recommendations