A SIMPLE ANALYTIC APPROACH FOR TRACKING RETINAL VESSELS AND MEASURING THEIR DIAMETERS

Zafer Yavuz, Cevat Ikibas, Cemal Kose

Abstract

Retinal image processing provides tools for automatic diagnosis and monitoring of retinal diseases such as diabetic retinopathy (DR), age related macular degeneration (ARMD), glucoma and such. The properties of vessel structures on the other hand are widely utilized in locating morphologic structures such as optic disc and macula and in automatic diagnosis of the retinal diseases. Due to the importance of retinal vessels, we propose a simple approach for vessel tracking and measuring vessel diameter in retinal fundus images. Images having manually segmented retinal vasculatures are obtained from STARE database and used in this study. Our method first finds the midlines of the vessel network on the segmented images by employing Zhang-Suen thinning algorithm and then tracks the vessel branches through those midlines. Lastly, the diameters of the vessel segments in different parts of the vasculature are calculated along with the tracking operation. The performed test results show that the proposed automatic method is quite successfully tracks the vessel network and measure the diameter.

References

  1. American Academy of Ophthalmology, (1991). Ophthalmic Pathology, (Section 11, pp 179), Basic and Clinical Science Courses.
  2. Gao, X. W., Bharath, A., Stanton, A., Hughes, A., Chapman, N., Thom, S., (2000). Quantification and Characterisation of Arteries in Retinal Images. (Vol. 63, Num. 2, pp. 133-146(14)), Computer Methods and Programs in Biomedicine.
  3. Gao, X, Bharath, A, Stanton, A, Hughes, A, Chapman, Thom, (2001). Measurement of Vessel Diameters on Retinal Images for Cardiovascular Studies. On-line Conference Proceedings: Medical Image Understanding and Analysis.
  4. Hutchins, G.M., Miner, M.M., Boitnott., J.K., (1976). Vessel Calibre and Branch-Angle of Human Coronary Artery Branch-Points, (Vol. 38, pp 572), Circulation Research.
  5. Köse, C., (2006). Fully Automatic Segmentation of Coronary Vessel Structures in Poor Quality X-ray Angiograms Images, (Vol. LNCS 4109, pp. 72-82), Springer: Lecture Notes in Compute Science.
  6. Köse, C., and Ikibas, C., (2008). Segmentation of Coronary Vessel Structures in X-ray Angiogram Images by Using Spatial Pattern Matching Method, (pp. 1-6), ISCIS2008.
  7. Köse, C., Sevik, U., and Gençalioglu, O., (2008). Automatic segmentation of age-related macular degeneration in retina fundus images, (Vol. 38, pp. 611-619), Computers in Biology and Medicine.
  8. Köse, C., Sevik, U., Gençalioglu, O., Ikibas, C., and Kayikçioglu, T., (2008). A Statistical Segmentation Method for Measuring Age-Related Macular Degeneration in Retinal Fundus Images, Journal of Medical Systems. doi: 10.1007/s10916-008-9210-4.
  9. Köse, C., Gençalioglu, O., and Sevik, U., (2009). An Automatic Diagnosis Method for the Knee Meniscus Tears in MR Images, (Vol. 36, pp. 1208-1216), Expert System With Applications.
  10. Lowell, J, Hunter, A, Steel, D, Basu, A, Ryder, R, Kennedy, (2004). Measurement of Retinal Vessel Widths from Fundus Images Based on 2D Modeling, Ieee Transactions On Medical Imaging.
  11. Martin, A., Tosunoglu, S., (2000). Image Processing Techniques for Machine Vision, Florida Conference on Recent Advances in Robotics, Boca Raton, FL: Florida Atlantic University.
  12. Newsom, R. S. B., Sullivan, P. M., Rassam, S. M. B., Jagoe R., Kohner, E. M., (1992). Retinal Vessel Measurement: Comparison between Observer and Computer Driven Methods, (Vol. 230, pp. 221-225), Graefe's archive for clinical and experimental ophthalmology.
  13. Pappas, T.N., and Lim, J.S., (1988). A New Method for Estimation of Coronary Artery Dimensions in hgiograms, (Vol. 36, pp. 1501-1512). IEEE Trans. On Acoust. Sp. And Sign. Proc.
  14. Parker, J., R., (1994). Practical Computer Vision using C, Wiley Computer Publishing.
  15. Ritter, G., X., Wilson, J., N., (1996). Handbook of Computer Vision Algorithms in Image Algebra, CRC Press.
  16. Russ, J. C., (1992). The Image Processing Handbook, CRC Press.
  17. Sonka, M., Hlavac, V., Boyle, R., (1998). Image Processing, Analysis, and Machine Vision, 2nd Edition, Pws. Pub. Co.
  18. Stanton, A.V., Wasan, B., Cerutti, A., Ford, S., Marsh, R., Sever, P.P., Thom, S.A., Hughes, A.D., (1995). Vascular Network Changes in the Retinal with Age and Hypertension, (Vol.13, pp 1724), J. Hypertens.
  19. STARE Project, Retrieved 20 March 2009 from http://www.parl.clemson.edu/stare/.
Download


Paper Citation


in Harvard Style

Yavuz Z., Ikibas C. and Kose C. (2010). A SIMPLE ANALYTIC APPROACH FOR TRACKING RETINAL VESSELS AND MEASURING THEIR DIAMETERS . In Proceedings of the First International Conference on Bioinformatics - Volume 1: BIOINFORMATICS, (BIOSTEC 2010) ISBN 978-989-674-019-1, pages 13-18. DOI: 10.5220/0002694200130018


in Bibtex Style

@conference{bioinformatics10,
author={Zafer Yavuz and Cevat Ikibas and Cemal Kose},
title={A SIMPLE ANALYTIC APPROACH FOR TRACKING RETINAL VESSELS AND MEASURING THEIR DIAMETERS},
booktitle={Proceedings of the First International Conference on Bioinformatics - Volume 1: BIOINFORMATICS, (BIOSTEC 2010)},
year={2010},
pages={13-18},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002694200130018},
isbn={978-989-674-019-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Bioinformatics - Volume 1: BIOINFORMATICS, (BIOSTEC 2010)
TI - A SIMPLE ANALYTIC APPROACH FOR TRACKING RETINAL VESSELS AND MEASURING THEIR DIAMETERS
SN - 978-989-674-019-1
AU - Yavuz Z.
AU - Ikibas C.
AU - Kose C.
PY - 2010
SP - 13
EP - 18
DO - 10.5220/0002694200130018