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Robust Methodology for Fractal Analysis and Recognition of the Retinal Vasculature
Abstract
Now a days in medical field we are facing many
problems in recognizing the retina images. To recognize the retinal
vasculature image they used many methods which are having many
disadvantages. But here we have used three methods for recognizing
which are box counting algorithm, differential box counting
algorithm and Fourier fractal dimension algorithm. Of these we have
got the best method for recognizing the retina by the fractal
dimension .Fractal dimension is computed on 100 images and which
is used for recognition purpose while giving the test input image.
First method needs segmentation and this method takes more time to
calculate the fractal dimension and computational cost is also so high.
Differential box counting algorithm has the same drawback what box
counting method had. So we used Fourier fractal dimension which
contain the pre processing, enhancement process (using Gabor
wavelet transform) and got the best recognition by using this method.
Keywords
References
G. Liew, J. Wang, P. Mitchell, and T. Wong, "Retinal vascular imaging:
a new tool in microvascular disease research," Circulation:
Cardiovascular Imaging, vol. 1, p. 156, 2008
M. B. M. Mendonça, C. A. A. Garcia, R. A. Nogueira, M. A. F. Gomes,
M. M. Valença, and F. Oréfice, "Fractal analysis of retinal vascular tree:
segmentation and estimation methods," Arquivos Brasileiros de
Oftalmologia, vol. 70, pp. 413-422, 2007.
F. Family, B. R. Masters, and D. E. Platt, "Fractal pattern formation in
human retinal vessels," Physica D: Nonlinear Phenomena, vol. 38, pp.
-103, 1989.
Jian Lia, QianDub, CaixinSuna” An improved box-counting method for
image fractal dimension estimation” Pattern Recognition 42 (2009) 2460
– 2469
Lewis A. Lipsitz, MD, Ary L. Goldberger, MD” Loss of 'Complexity'
and AgingPotential Applications of Fractals and Chaos Theory to
Senescence” (JAMA. 1992;267:1806-1809)
Pentland, A., and Choudhury, T. Face recognition for smart
environments. Computer 33(2): 50-55, 2000.
Phillips, P.J., Moon, H., Rizvi, S.A., and Rauss, P.J. The FERET
evaluation methodology for face-recognition algorithms. Trans. Pat.
Anal. Mach. Intel. 22(10): 1090-1104, 2000.
A. Wong, L. Wu, P.B. Gibbons, and C. Faloutsos, “Fast estimation of
fractal dimension and correlation integral on stream data”, Information
Processing Letters, vol. 93, pp. 91-97, 2005.
M. Z. Che Azemin, D. K. Kumar, T. Y. Wong, R. Kawasaki, P.
Mitchell, and J.J. Wang,J2010 “Robust Methodology for Fractal
Analysis of the Retinal Vasculature”Vol30,no 2,pp 243-250
Deepa Sankar, Tessamma Thomas” Fractal Features based on
Differential Box Counting Method for the Categorization of Digital
Mammograms” Vol.2 (2010), pp.011-019
A. Osareh and B. Shadgar” Automatic blood vessel segmentation in
color images of retina” Vol. 33, No. B2, pp 191-206
Yuan Y. Tang, Yu Tao, Ernest C.M. Lam” New methodfor feature
extraction basedon fractal behavior” Pattern Recognition 35 (2002)
–1081
T. Y. Wong, R. Klein, A. R. Sharrett, B. B. Duncan, D. J. Couper, J. M.
Tielsch, B. E. K. Klein, and L. D. Hubbard, "Retinal arteriolar
narrowing and risk of coronary heart disease in men and women: the
Atherosclerosis Risk in Communities Study," Jama, vol. 287, p. 1153,
L. Gang, O. Chutatape, and S. M. Krishnan, "Detection and
measurement of retinal vessels in fundus images using amplitude
modified second-order Gaussian filter," IEEE Transactions on
Biomedical Engineering, vol. 49, pp. 168-172, 2002.
J. V. B. Soares, J. J. G. Leandro, R. M. Cesar Jr, H. F. Jelinek, and M. J.
Cree, "Retinal vessel segmentation using the 2-D Gabor wavelet and
supervised classification," IEEE Transactions on Medical Imaging, vol.
, pp. 1214-1222, 2006
J. Jan. Medical Image Processing, Reconstruction and Restoration:
Concepts and Methods. Signal Processing and Communications. Taylor
& Francis, 2006.
C. S. Kenney, M. Zuliani, and B. S. Manjunath. An axiomatic approach
to corner detection. IEEE CVPR, 1:191–197, 2005
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