Automatic Localization and Segmentation of Blood Vessels, Optic Disc, and Macula in Digital Fundus Images

  • S. Balasubramanian
  • Anantha Vidya Sagar
  • G. Vijaya Saradhi
  • V. Chandrasekaran
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 4)

One of the major areas of medical research is the design and implementation of intelligent decision support systems for medical professionals. In this context, digital medical image analysis plays an important role in building computational tools to assist physicians in quantification and visualization of pathology and anatomical structures. Such tools will help the medial community to diagnose disorders and treat patients more effectively than before.

Digital fundus images are the images of the fundus occuli acquired using a fundus camera where the optic system of the camera is connected to a CCD. The visible part of the image consists of the retina with its vascular network and the optic nerve head. Study of digital fundus images is important in relation to the diagnosis of diabetic retinopathy (DR), a leading cause of blindness among diabetic patients.


Diabetic Retinopathy Active Contour Retinal Image Fundus Image Retinal Blood 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.


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  1. 1.
    Abdel-Ghafar RA, Morris T, Ritchings T, Wood I (2004) Detection and characterisation of the optic disk in glaucoma and diabetic retinopathy. In: Proc of medical image understanding and analysis, LondonGoogle Scholar
  2. 2.
    Abraham Chandy D, Vijaya Kumari V (2006) Genetic algorithm based location of optic disc in retinal images. Academic Open Internet Journal 17Google Scholar
  3. 3.
    Mendonca AM, Campilho A (2006) Segmentation of retinal blood vessesl by combining the detection of centerlines and morphological reconstruction. IEEE Tran Med Imag 25: 1200–1213CrossRefGoogle Scholar
  4. 4.
    Kirbas C, Quek FKH (2003) Vessel extraction techniques and algorithms: a survey. In: Third IEEE symposium on bioinformatics and bioengineering, pp 238–245Google Scholar
  5. 5.
    Chanwimaluang T, Fan G (2003) An Efficient blood vessel detection algorithm for retinal images using local entropy thresholding. In: Proc IEEE international symposium on circuits and systems, pp V-21–V-24Google Scholar
  6. 6.
    Chaudhuri S, Chatterjee S, Katz N, Nelson M, Goldbaum M (1989) Detection of blood vessels in retinal images using two-dimensional matched filters. IEEE Trans Med Imag 8:263–269CrossRefGoogle Scholar
  7. 7.
    Dua S, Kandiraju N, Thompson HW (2005) Design and implementation of a unique blood-vessel detection algorithm towards early detection of diabetic retinopathy. In: Proc of the IEEE international conference on information technology, pp 26–31Google Scholar
  8. 8.
    Foracchia M, Grisan E, Ruggeri A (2004) Detection of OD in retinal images by means of a geometrical model of vessel structure. IEEE Trans Med Imag 23:1189–1194CrossRefGoogle Scholar
  9. 9.
    Gagnon L, Lalonde M, Beaulieu M, Boucher MC (2001) Procedure to detect anatomical structures in optical fundus images. In: Proc SPIE Med Imag: Image processing, pp 1218–1225Google Scholar
  10. 10.
    Hoover A, Goldbaum M (2003) Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels. IEEE Trans Med Imag 22:951–958CrossRefGoogle Scholar
  11. 11.
    Hoover A, Kouznetsova V, Goldbaum M (2000) Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response. IEEE Trans Med Imag 19:203–211CrossRefGoogle Scholar
  12. 12.
    Huiqi L, Opas C (2001) Automatic location of optic disc in retinal images. In: Proc of the International conference on image processing, pp 837–840Google Scholar
  13. 13.
    Kaupp A, Dolemeyer A, Wilzeck R, Schlosser R, Wolf S, Meyer-Ebrecht D (1994) Measuring morphological properties of the human retinal vessel system using a two-stage image processing approach. In: Proc IEEE international conference on image processing, pp 431–435Google Scholar
  14. 14.
    Koozekanani D, Boyer C, Roberts C, Katz S (2001) Tracking the optic nerve in OCT video using dual eigenspaces and an adaptive vascular distribution model. In: Proc IEEE conf computer vision and pattern recognition, pp 1934–1941Google Scholar
  15. 15.
    Lalonde M, Beaulieu M, Gagnon L (2001) Fast and robust optic disk detection using pyramidal decomposition and Hausdorff-based template matching. IEEE Trans Med Imag 20: 1193–1200CrossRefGoogle Scholar
  16. 16.
    Li H, Chutatape O (2004) Automated feature extraction in color retinal images by a model based approach. IEEE Biomed Eng 51:246–254CrossRefGoogle Scholar
  17. 17.
    Lowell J, Hunter A, Steel D, Basu A, Ryder R, Fletcher E, Kennedy L (2004) Optic nerve head segmentation. IEEE Trans Med Imag 23(2):256–264CrossRefGoogle Scholar
  18. 18.
    Mendels F, Heneghan C, Thiran JP (1999) Identification of the optic disc boundary in retinal images using active contours. In: Proc IMVIP Conference, pp 103–115Google Scholar
  19. 19.
    Park M, Jesse SJ, Luo S (2006) Locating the optic disc in retinal images. In: Proc international conference on computer graphics, imaging and visualisation, pp 141–145Google Scholar
  20. 20.
    Neimeijer M (2006) Automatic detection of diabetic retinopathy in digital fundus photographs. PhD thesis, Image Sciences Institute, University Medical Center Utrecht, Utrecht, The NetherlandsGoogle Scholar
  21. 21.
    Niemeijer M, Staal J, Van Ginneken B, Loog M, Abramoff MD (2004) Comparative study of retinal vessel segmentation methods on a new publicly available database. In: Filtzpatrick M, Sonka M (eds) Proc SPIE Med Imag, pp 648–656Google Scholar
  22. 22.
    Osareh A, Mirmehdi M, Thomas B, Markham R (2002) Comparison of colour spaces for optic disc localisation in retinal images. In: Proc 16th international conference on pattern recognition, pp 743–746Google Scholar
  23. 23.
    Pallawala PMDS, Hsu W, Lee ML, Au Eong K-G (2004) Automated optic disc localization and contour detection using ellipse fitting and wavelet transform. Springer Lecture Notes in Computer Science 3022:139–151CrossRefGoogle Scholar
  24. 24.
    Sinthanayothin C, Boyce JF, Cook HL, Williamson TH (1999) Automated localisation of the optic disc, fovea, and retinal blood vessels from digital colour fundus images. British Journal of Ophthalmology 83:902–910CrossRefGoogle Scholar
  25. 25.
    Staal J, Abramoff MD, Neimeijer M, Viergever MA, Van Ginneken B (2004) Ridge-based vessel segmentation in colour images of the retina. IEEE Trans Med. Imag 23:501–509CrossRefGoogle Scholar
  26. 26.
    Vijaya Saradhi G, Balasubramanian S, Chandrasekaran V (2006) Performance enhancement of optic disc boundary detection using active contours via improved homogenization of optic disc region. In: Proc of the international conference on information and automation, pp 264–269Google Scholar
  27. 27.
    Wareham N (1993) Cost-effectiveness of alternative methods for diabetic retinopathy screening (letter). Diabetic Care 16:844Google Scholar
  28. 28.
    Yulong M, Dingru X (1990) Recognizing the glaucoma from ocular fundus by image analysis. In: Proc annual international conference of the IEEE engineering in medicine and biology society, pp 178–179Google Scholar
  29. 29.
    Zana F, Klein JC (2001) Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation. IEEE Trans Med Imag 11:1111–1119Google Scholar
  30. 30.
    Chin ZY, Abidi BR, Page DL, Abidi MA (2006) Gray-level grouping (GLG): an automatic method for optimized image contrast enhancement —part I: the basic method. IEEE Trans Image Process 15:2290–2302CrossRefGoogle Scholar
  31. 31.
  32. 32.
  33. 33.
  34. 34.
  35. 35.
  36. 36.
  37. 37.

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • S. Balasubramanian
    • 1
  • Anantha Vidya Sagar
    • 1
  • G. Vijaya Saradhi
    • 1
  • V. Chandrasekaran
    • 1
  1. 1.Department of Mathematics and Computer ScienceSri Sathya Sai UniversityIndia

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