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International Journal of Information Technology & Computer Science ( IJITCS )

Abstract :

Retinopathy of Prematurity (ROP) is a common retinal neovascular disorder of premature infants. It can  be characterized by inappropriate and disorganized vessel. This paper presents a method for blood vessel  detection on infant retinal images. We proposed a set of automatic methods to extract skeletonized  structure of premature infant’s low-contrast retinal blood vessel network. The method is composed of  four steps : Statistically optimized Laplacian of Guassian filter for edge detection, Medial Axis  Skeletonization, Image Pruning, and Spur Removal by morphological Opening. The algorithm has been  applied to test on 40 infant retinal images. The result from the algorithm was compared with  ophthalmologists’ hand-drawn ground truth and it can detect the blood vessel with a high specificity of  0.913 and sensitivity of 0.982

Keywords :

: Vessel Detection, Laplacian of Gaussian , Infant Retinal Images

References :

  1. S. C. Chaudhuri, N. Katz, M. Nelson, and M. Goldbaum, “Detection of blood vessels in retinal images using two dimensional blood vessel filters”, IEEE Trans. on Med. Img., vol.8, September 1989.
  2. S.L. Wood, G. Qu, and L.W. Roloff, “Detection and labeling of retinal vessels for longitidunal studies”, in IEEE Int. Conf. on Image Processing, vol. 3, pp. 164–167, 1995.
  3. F. Mao, S. Ruan, A. Bruno, C. Toumoulin, R. Collorec, and P. Haigron, “Extraction of structural features in digital subtraction angiography”, in IEEE Int. Biomed. Eng. Days, pp.166–169, 1992.
  4. A. Hoover, V. Kouznetsova, and M. Goldbaum, “Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response”, IEEE Trans. on Med. Img., vol. 19, pp. 203–210, March 2000.
  5. Y. Tolias and S.M. Panas, “A fuzzy vessel tracking algorithm for retinal images based on fuzzy clustering”, IEEE Trans. on Med. Img., vol. 17, pp. 263–273, April 1998.
  6. L. Zhou, M.S. Rzeszotarski, L.J. Singerman, and J.M. Chokreff, “The detection and quantification of retinopathy using digital angiograms”, IEEE Trans. on Med. Img., vol. 13, pp.619–626, December 1994.
  7. M. Goldbaum, S. Moezzi, A. Taylor, S. Chatterjee, J. Boyd, E. Hunter, and R. Jain, “Automated diagnosis and image understanding with object extraction, object classification, and inferencing in retinal images”, in IEEE Int. Conf. on Image Processing, 1996.
  8. J. J. Staal, S. N. Kalitzin, M. D. Abramoff, T. Berendschot, B.van Ginneken, M. A. Viergever, "Classifying convex sets for vessel detection in retinal images", Proceedings of the IEEE International Symposium on Biomedical Imaging, 2002, pp. 269-272
  9. R. Pai, A. Hoover and M. Goldbaum, “Automated Diagnosis of Reginal Images Using Evidential Reasoning”, in the 15th Int'l Conf. on Systems Engineering, Las Vegas, NV, August 2002.
  10. N. Otsu, “A Threshold Selection Method from Gray-Level Histograms,” IEEE Transactions on Systems, Man and Cybernetics, vol. 9, no. 1, pp. 62-66, 1979.
  11. R. M. Haralick, L. G. Shapiro, “Computer and Robot Vision,” Addison-Wesley Publishing Compang, Vol.I, pp. 346-349.

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