Comparison of Central Light Reflex Width-to-Retinal Vessel Diameter Ratio between Glaucoma and Normal Eyes by Using Edge Detection Technique

Glaucoma is a disease that causes visual loss in adults. Glaucoma causes damage to the optic nerve and its overall pathophysiology is still not fully understood. Vasculopathy may be one of the possible causes of nerve damage. Photographic imaging of retinal vessels by fundus camera during eye examination may complement clinical management. This paper presents an innovation for measuring central light reflex width-to-retinal vessel diameter ratio (CRR) from digital retinal photographs. Using our edge detection technique, CRRs from glaucoma and normal eyes were compared to examine differences and associations. CRRs were evaluated on fundus photographs of participants from Mettapracharak (Wat Raikhing) Hospital in Nakhon Pathom, Thailand. Fifty-five photographs from normal eyes and twenty-one photographs from glaucoma eyes were included. Participants with hypertension were excluded. In each photograph, CRRs from four retinal vessels, including arteries and veins in the inferotemporal and superotemporal regions, were quantified using edge detection technique. From our finding, mean CRRs of all four retinal arteries and veins were significantly higher in persons with glaucoma than in those without glaucoma (0.34 vs. 0.32, p < 0.05 for inferotemporal vein, 0.33 vs. 0.30, p < 0.01 for inferotemporal artery, 0.34 vs. 0.31, p < 0.01 for superotemporal vein, and 0.33 vs. 0.30, p < 0.05 for superotemporal artery). From these results, an increase in CRRs of retinal vessels, as quantitatively measured from fundus photographs, could be associated with glaucoma.

• P. Siriarchawatana
• K. Leungchavaphongse
• N. Covavisaruch
• K. Rojananuangnit
• P. Boondaeng
• N. Panyayingyong

• Glaucoma
• retinal vessel
• central light reflex
• image processing
• fundus photograph
• edge detection.

[1] K. Papastathopoulos, J. Jonas, “Follow up of focal narrowing of retinal arterioles in glaucoma,” The British Journal of Ophthalmolo, vol. 83, no. 3, pp. 285-289, 1999.
[2] N. Amerasinghe, T. Aung, N, “Cheung, et al. Evidence of retinal vascular narrowing in glaucomatous eyes in an Asian population,” Invest Ophthalmol Vis Sci, vol. 49, no. 12, pp. 5397–5402, 2008.
[3] M. Gunn, “On ophthalmoscopic evidence of general arterial disease,” Trans Ophthalmol Soc UK, pp. 356-381, 1898.
[4] O. Brinchmann-Hansen, K. Myhre, K. Dahl-Jørgensen, K. F. Hanssen, L. Sandvik, “The central light reflex of retinal arteries and veins in insulin-dependent diabetic subjects,” Acta Ophthalmol (Copenh), vol. 65, no. 4, pp. 474-480, 1987.
[5] O. Brinchmann-Hansen, C. C. Christensen, K. Myhre, “The response of the light reflex of retinal vessels to reduced blood pressure in hypertensive patients,” Acta Ophthalmologica, vol. 68, no. 2, pp. 155–161, 1990.
[6] O. Brinchmann-Hansen, K. Myhre, “The effect of hypoxia on the central light reflex of retinal arteries and veins,” Acta Ophthalmologica, pp. 249–255. 1989.
[7] A. Bhuiyan, C. Y. Cheung, S. Frost, E. Lamoureux, P. Mitchell, Y. Kanagasingam, T. Y. Wong, “Development and reliability of retinal arteriolar central light reflex quantification system: a new approach for severity grading,” Invest Ophthalmol Vis Sci, vol. 67, no. 3, pp. 7975-7981, Oct 2014.
[8] P. C. Siddalingaswamy, K. Gopalakrishna Prabhu, “Automatic Localization and Boundary Detection of Optic Disc Using Implicit Active Contours,” International Journal of Computer Applications, vol. 1, no. 6, pp. 1–5, Feb 2010.
[9] L. D. Hubbard, R. J. Brothers, W. N. King, L. X. Clegg, R. Klein, L. S. Cooper, A. R. Sharrett, M. D. Davis, J. Cai, “Methods for evaluation of retinal microvascular abnormalities associated with hypertension/sclerosis in the Atherosclerosis Risk in Communities Study,” Ophthalmology, vol. 106, no. 12, pp. 2269-2280, Dec 1999.
[10] K. Zuiderveld. “Contrast limited adaptive histogram equalization,” Graphics gems IV, pp. 474-485, 1994
[11] P. Perona, J. Malik, “Scale-space and edge detection using anisotropic diffusion,” IEEE Trans. PAMI, vol. 12, no. 7, pp. 629-639, July 1990.
[12] A.F. Frangi, W.J. Niessen, K.L. Vincken, M.A. Viergever, “Multiscale vessel enhancement filtering,” In Medical Image Computing and Computer-Assisted Intervention - MICCAI'98, vol. 1496, pp. 130-137, 1998.
[13] 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.
[14] R. C. Gonzalez, R. E.Woods. Digital Image Processing. Upper Saddle River, NJ: Pearson Prentice Hall, 2008.
[15] J. Canny, “A computational approach to edge detection,” IEEE PAMI, vol. 8, no. 6, pp. 679-698, 1986.
[16] L. Lam, S. Lee, C. Suen. “Thinning methodologies-a comprehensive survey,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, no.9, pp. 879, Sep 1992.