Computerized Medical Imaging and Graphics
Volume 34, Issue 3 , Pages 228-235 , April 2010

A coarse-to-fine strategy for automatically detecting exudates in color eye fundus images

  • Daniel Welfer

      Affiliations

    • Instituto de Informática, Universidade Federal do Rio Grande do Sul, Av. Bento Gonalves 9500, Porto Alegre, RS, CEP 91509-900, Brazil
  • ,
  • Jacob Scharcanski

      Affiliations

    • Instituto de Informática, Universidade Federal do Rio Grande do Sul, Av. Bento Gonalves 9500, Porto Alegre, RS, CEP 91509-900, Brazil
    • Corresponding Author InformationCorresponding author. Tel.: +55 51 3308 7128; fax: +55 51 3308 7308.
  • ,
  • Diane Ruschel Marinho

      Affiliations

    • Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos, 2400, Porto Alegre, RS, CEP 90035-003, Brazil

Received 29 May 2009 ,Revised 9 October 2009 ,Accepted 12 October 2009.

References 

  1. Frith P, Gray R, MacLennan S, Ambler P. The eye in clinical practice. 2nd ed.. London: Blackwell Science Ltd; 2001;
  2. Laser photocoagulation: ocular research and therapy in diabetic retinopathy. In: Hollyfield JG, Anderson RE, LaVail MM, editors. Retinal degenerative diseases. Springer; 2006. p. 195–200.
  3. Retinal vascular disease. In: Tasman W, Jaeger EA, editors. The Wills eye hospital atlas of clinical ophthalmology. Lippincott Williams and Wilkins Publ.; 2001. p. 210.
  4. Ciulla TA, Amador AG, Zinman B. Diabetic retinopathy and diabetic macular edema. Diabetes Care. 2003;26(9):2653–2664
  5. Walter T, Klein J-C, Massin P, Erginay A. A contribution of image processing to the diagnosis of diabetic retinopathy – detection of exudates in color fundus images of the human retina. Transactions on Medical Imaging. 2002;21(10):1236–1243
  6. Lalonde M, Laliberté F, Gagnon L. RetsoftPlus: a tool for retinal image analysis. In: Proceedings of the 17th IEEE symposium on computer-based medical systems (CBMS’04). IEEE; 2004;p. 542–547
  7. Sopharak A, Uyyanonvara B, Barmanb S, Williamson TH. Automatic detection of diabetic retinopathy exudates from non-dilated retinal images using mathematical morphology methods. Computerized Medical Imaging and Graphics. 2008;32:720–727
  8. Köse C, Şevik U, Gençaliağlu O. Automatic segmentation of age-related macular degeneration in retinal fundus images. Computers in Biology and Medicine. 2008;38:611–619
  9. Osareh A, Mirmehdi M, Thomas B, Markham R. Automated identification of diabetic retinal exudates in digital colour images. British Journal of Ophthalmology. 2003;87:1220–1223
  10. Osareh A, Mirmehdi M, Thomas B, Markham R. Automatic recognition of exudative maculopathy using fuzzy c-means clustering and neural networks. In: Claridge JBE, editor. Medical image understanding and analysis; 2001. p. 49–52.
  11. Osareh A, Mirmehdi M, Thomas B, Markham R. Classification and localisation of diabetic-related eye disease. In: Heyden MNPJA, Sparr G, editors. 7th European conference on computer vision. 2002. p. 502–16.
  12. Osareh A, Mirmehdi M, Thomas B, Markham R. Comparative exudate classification using support vector machines and neural networks. In: Dohi RKT, editor. 5th international conference on medical image computing and computer-assisted intervention. 2002. p. 413–20.
  13. Sopharak A, Uyyanonvara B, Barman S. Automatic exudate detection from non-dilated diabetic retinopathy retinal images using fuzzy c-means clustering. Sensors. 2009;9:2148–2161
  14. Kauppi T, Kalesnykiene V, Kämäräinen J-K, Lensu L, Sorri I, Raninen A, et al. DIARETDB1: diabetic retinopathy database and evaluation protocol. In: Medical image understanding and analysis (MIUA). 2007. p. 61–5.
  15. Jähne B, Haußecker H, Geißler P. Handbook of computer vision and applications: signal processing and pattern recognition, vol. 2. New York: Academic Press; 1999;
  16. Soille P. Morphological image analysis: principles and applications. 2nd ed.. Heidelberg: Springer; 2003;
  17. Dougherty ER, Lotufo RA. Hands-on morphological image processing, vol. TT59. SPIE Publications; 2003;
  18. Shih FY. Image processing and mathematical morphology fundamentals and applications. New York: CRC Press; 2009;
  19. Seo JM, Kim KK, Kim JH, Park KS, Chung H. Measurement of ocular torsion using digital fundus image. In: Proceedings of the 26th annual international conference of the IEEE EMBS. 2004;p. 1711–1713
  20. Kande GB, Subbaiah P, Savithri T. Segmentation of exudates and optic disc in retinal images. In: Sixth Indian conference on computer vision, graphics & image processing, 2008. ICVGIP. Bhubaneswar, India: IEEE Computer Society; 2008;p. 535–542
  21. Lupaşcu CA, Tegolo D, Rosa LD. Automated detection of optic disc location in retinal images. In: 21st IEEE international symposium on computer-based medical systems. IEEE; 2008;p. 17–22
  22. Welfer D, Scharcanski J, Kitamura CM, Pizzol MMD, Ludwig LWB, Marinho DR. Segmentation of the optic disk in color eye fundus images using an adaptive morphological approach, Tech. Rep., Instituto de Informática, UFRGS (January 2009).
  23. Torsten Schlote JM, Grueb M, Rohrbach JM. Pocket atlas of ophthalmology. New York: Georg Thieme Verlag; 2006;

PII: S0895-6111(09)00129-3

doi: 10.1016/j.compmedimag.2009.10.001

Computerized Medical Imaging and Graphics
Volume 34, Issue 3 , Pages 228-235 , April 2010