{"title":"Comparison of Central Light Reflex Width-to-Retinal Vessel Diameter Ratio between Glaucoma and Normal Eyes by Using Edge Detection Technique ","authors":"P. Siriarchawatana, K. Leungchavaphongse, N. Covavisaruch, K. Rojananuangnit, P. Boondaeng, N. Panyayingyong","volume":116,"journal":"International Journal of Biomedical and Biological Engineering","pagesStart":430,"pagesEnd":434,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10005791","abstract":"
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<\/em>. 0.32, p<\/em> < 0.05 for inferotemporal vein, 0.33 vs<\/em>. 0.30, p<\/em> < 0.01 for inferotemporal artery, 0.34 vs<\/em>. 0.31, p <\/em>< 0.01 for superotemporal vein, and 0.33 vs<\/em>. 0.30, p<\/em> < 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>\r\n","references":"[1]\tK. Papastathopoulos, J. Jonas, \u201cFollow up of focal narrowing of retinal arterioles in glaucoma,\u201d The British Journal of Ophthalmolo, vol. 83, no. 3, pp. 285-289, 1999.\r\n[2]\tN. Amerasinghe, T. Aung, N, \u201cCheung, et al. Evidence of retinal vascular narrowing in glaucomatous eyes in an Asian population,\u201d Invest Ophthalmol Vis Sci, vol. 49, no. 12, pp. 5397\u20135402, 2008.\r\n[3]\tM. Gunn, \u201cOn ophthalmoscopic evidence of general arterial disease,\u201d Trans Ophthalmol Soc UK, pp. 356-381, 1898.\r\n[4]\tO. Brinchmann-Hansen, K. Myhre, K. Dahl-J\u00f8rgensen, K. F. Hanssen, L. Sandvik, \u201cThe central light reflex of retinal arteries and veins in insulin-dependent diabetic subjects,\u201d Acta Ophthalmol (Copenh), vol. 65, no. 4, pp. 474-480, 1987.\r\n[5]\tO. Brinchmann-Hansen, C. C. Christensen, K. Myhre, \u201cThe response of the light reflex of retinal vessels to reduced blood pressure in hypertensive patients,\u201d Acta Ophthalmologica, vol. 68, no. 2, pp. 155\u2013161, 1990.\r\n[6]\tO. Brinchmann-Hansen, K. Myhre, \u201cThe effect of hypoxia on the central light reflex of retinal arteries and veins,\u201d Acta Ophthalmologica, pp. 249\u2013255. 1989.\r\n[7]\tA. Bhuiyan, C. Y. Cheung, S. Frost, E. Lamoureux, P. Mitchell, Y. Kanagasingam, T. Y. Wong, \u201cDevelopment and reliability of retinal arteriolar central light reflex quantification system: a new approach for severity grading,\u201d Invest Ophthalmol Vis Sci, vol. 67, no. 3, pp. 7975-7981, Oct 2014.\r\n[8]\tP. C. Siddalingaswamy, K. Gopalakrishna Prabhu, \u201cAutomatic Localization and Boundary Detection of Optic Disc Using Implicit Active Contours,\u201d International Journal of Computer Applications, vol. 1, no. 6, pp. 1\u20135, Feb 2010. \r\n[9]\tL. D. Hubbard, R. J. Brothers, W. N. King, L. X. Clegg, R. Klein, L. S. Cooper, A. R. Sharrett, M. D. Davis, J. Cai, \u201cMethods for evaluation of retinal microvascular abnormalities associated with hypertension\/sclerosis in the Atherosclerosis Risk in Communities Study,\u201d Ophthalmology, vol. 106, no. 12, pp. 2269-2280, Dec 1999.\r\n[10]\tK. Zuiderveld. \u201cContrast limited adaptive histogram equalization,\u201d Graphics gems IV, pp. 474-485, 1994\r\n[11]\tP. Perona, J. Malik, \u201cScale-space and edge detection using anisotropic diffusion,\u201d IEEE Trans. PAMI, vol. 12, no. 7, pp. 629-639, July 1990.\r\n[12]\tA.F. Frangi, W.J. Niessen, K.L. Vincken, M.A. Viergever, \u201cMultiscale vessel enhancement filtering,\u201d In Medical Image Computing and Computer-Assisted Intervention - MICCAI'98, vol. 1496, pp. 130-137, 1998.\r\n[13]\tN. Otsu, \u201cA Threshold Selection Method from Gray-Level Histograms,\u201d IEEE Transactions on Systems, Man, and Cybernetics, vol. 9, no. 1, pp. 62-66, 1979.\r\n[14]\tR. C. Gonzalez, R. E.Woods. Digital Image Processing. Upper Saddle River, NJ: Pearson Prentice Hall, 2008.\r\n[15]\tJ. Canny, \u201cA computational approach to edge detection,\u201d IEEE PAMI, vol. 8, no. 6, pp. 679-698, 1986.\r\n[16]\tL. Lam, S. Lee, C. Suen. \u201cThinning methodologies-a comprehensive survey,\u201d IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, no.9, pp. 879, Sep 1992.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 116, 2016"}