Optical Verification of an Ophthalmological Examination Apparatus Employing the Electroretinogram Function on Fundus-Related Perimetry

Authors: Naoto Suzuki

Abstract:

Japanese are affected by the most common causes of eyesight loss such as glaucoma, diabetic retinopathy, pigmentary retinal degeneration, and age-related macular degeneration. We developed an ophthalmological examination apparatus with a fundus camera, precisely fundus-related perimetry (microperimetry), and electroretinogram (ERG) functions to diagnose a variety of diseases that cause eyesight loss. The experimental apparatus was constructed with the same optical system as a fundus camera. The microperimetry optical system was calculated and added to the experimental apparatus using the German company Optenso's optical engineering software (OpTaliX-LT 10.8). We also added an Edmund infrared camera (EO-0413), a lens with a 25 mm focal length, a 45° cold mirror, a 12 V/50 W halogen lamp, and an 8-inch monitor. We made the artificial eye of a plane-convex lens, a black spacer, and a hemispherical cup. The hemispherical cup had a small section of the paper at the bottom. The artificial eye was photographed five times using the experimental apparatus. The software was created to display the examination target on the monitor and save examination data using C++Builder 10.2. The retinal fundus was displayed on the monitor at a length and width of 1 mm and a resolution of 70.4 ± 4.1 and 74.7 ± 6.8 pixels, respectively. The microperimetry and ERG functions were successfully added to the experimental ophthalmological apparatus. A moving machine was developed to measure the artificial eye's movement. The artificial eye's rear part was painted black and white in the central area. It was rotated 10 degrees from one side to the other. The movement was captured five times as motion videos. Three static images were extracted from one of the motion videos captured. The images display the artificial eye facing the center, right, and left directions. The three images were processed using Scilab 6.1.0 and Image Processing and Computer Vision Toolbox 4.1.2, including trimming, binarization, making a window, deleting peripheral area, and morphological operations. To calculate the artificial eye's fundus center, we added a gravity method to the program to calculate the gravity position of connected components. From the three images, the image processing could calculate the center position.

Keywords: Ophthalmological examination apparatus, microperimetry, electroretinogram, eye movement.

References:

[1] K. Nakae, F. Kogure et al., "Recent epidemiological of the visual loss in Japan", Journal of Health and Welfare Statistics 38(7), 1991, pp13-22.
[2] T. Tsuchiya, "Measure Against Lifestyle Related Disease," JMAJ, Vol.49 No.3, 2006, pp.132-134.
[3] Z.T. Bloomgarden, "American Diabetes Association Annual Meeting, 1999, Diabetes and obesity," Diabetes Care, Vol.23, No.1, 2000, pp.118-124.
[4] N. Suzuki, "Development of Moving Multifocal Electroretinogram with a Precise Perimetry Apparatus", International Journal of Biomedical and Biological Engineering, Vol.13, No.11, 2019, pp465-469.
[5] M. Michaelides, D.M. Hunt, A.T. Moore, "The genetics of inherited macular dystrophies", J Med Genet, Vol.40 No.9, 2003, pp641-650.
[6] N Lois, G.E. Holder, C Bunce, F.W. Fitzke, A.C. Bird, "Phenotypic subtypes of Stargardt macular dystrophy-fundus flavimaculatus", Arch Ophthalmol, Vol.119 No.3, 2001, pp359-369.
[7] Y Miyake, K Ichikawa, Y Shiose, Y Kawase, "Hereditary Macular Dystrophy without Visible Fundus Abnormality", Am J Ophthalmol, Vol.108 No.3, 1989, pp292-299.
[8] C.J. Boon, B.J. Klevering, B.P. Leroy, C.B. Hoyng, J.E.E. Keunena, A.I. den Hollander, "The spectrum of ocular phenotypes caused by mutations in the BEST1 gene", Prog Retin Eye Res, Vol.28 No.3, 2009, pp187-205.
[9] J.J. Kanski, B. Bowling, "Macular Dystrophies" in Clinical Ophthalmology: Systematic Approach, 7th Edition, Amsterdam: Elsevier-Health Sciences Division, 2011, pp665-670.
[10] J.D. Gass, "Acute zonal occult outer retinopathy. Donders Lecture: The Netherlands Ophthalmological Society, Maastricht, Holland, June 19, 1992", J Clin Neuroophthalmol, No.13, 1993, pp79-97.
[11] J.J. Kanski, B. Bowling, "Acute zonal occult outer retinopathy" in Clinical Ophthalmology: Systematic Approach, 7th Edition, Amsterdam: Elsevier-Health Sciences Division, 2011, pp594-595.
[12] L.M. Jampol, P.A. Pugh et al, " Multiple evanescent white dot syndrome, 1. Clinical findings", Arch Ophthalmol, No.102, 1984, pp671-674.
[13] J.J. Kanski, B. Bowling, "Multiple evanescent white dot syndrome" in Clinical Ophthalmology: Systematic Approach, 7th Edition, Amsterdam Elsevier-Health Sciences Division, 2011, pp588-589.
[14] H. Samet, M. Tamminen, "Efficient Component Labeling of Images of Arbitrary Dimension Represented by Linear Bintrees", IEEE Transactions on Pattern Analysis and Machine Intelligence Vol.10, No.4, 1988, pp579-586.
[15] M.B. Dillencourt, H. Samet, M. Tamminen, "A general approach to connected-component labeling for arbitrary image representations", Journal of the ACM, Vol.39, No.2, 1992, pp253-280.
[16] K. Wu, W. Koegler, J. Chen, A. Shoshani, "Using bitmap index for interactive exploration of large datasets", 15th International Conference on Scientific and Statistical Database Management, Cambridge, MA, 2003, pp1-10.
[17] R. Fisher, S. Perkins, A. Walker, E. Wolfart, "Connected Component Labeling", 2003, Retrieved 15 July 2022.
[18] L.G. Shapiro, G.C. Stockman, " Computer Vision", Prentice Hall, 2001, pp.69–73.
[19] A. Gullstrand, “How I found the mechanism of intracapsular accommodation”, Nobel Lectures, Physiology or Medicine 1901, pp414-431.
[20] C. Gomez (Editor), "Engineering and Scientific Computing with Scilab", Birkhauser, 1999.
[21] P. Roux, "Scilab from theory to practice: I. Fundamentals", Scilab Enterprise, 2016.