A Novel Approach to Method for the Detection of Optic Disc Location in Retinal Images using Image Processing Techniques

Year 2016, Volume: 5 , 41 - 47, 07.11.2016

Kemal Adem , Mahmut Hekım , Onur Comert , Selim Demır

https://izlik.org/JA99AL94WC

Abstract

Biomedical image analysis used for which is applied to assist in clinical diagnosis processes, is one of the research areas that draw intense interest of scientists. The retinal fundus oculi images are used in clinics extensively for the diagnosis and treatment of various eye diseases. The detection of optic disc is one of the most basic steps that should be taken during automatic screening of Diabetic Retinopathy (DR) in particular. In this study, three different solutions are proposed for detecting the optic disc location, using the brightness and circularity properties of the related region. As a result of the comparison of the findings of these three experiments, the Circular Hough Transform method applied with HSV color space is was found to be more successful by 99.16% accuracy, and therefore it is proposed as a viable method for the detection of optic disc.

Keywords

Retina , optic disk , Image processing , Hough transform.

References

• R. Klein, B.E. Klein, S.E. Moss, M.D. Davis, D.L. DeMets, The Wisconsin epidemiologic study of diabetic retinopathy. III. Prevalence and risk of diabetic retinopathy when age at diagnosis is 30 or more years, Arch Ophthalmol, 102 527–532, 1984.
• J.W. Yau, S.L. Rogers, R. Kawasaki, Global prevalence and major risk factors of diabetic retinopathy, Diabetes Care, 35(3) 556-64, 2012.
• R. Hiller, R.D. Sperduto, M.J. Podgor, F.L. Ferris, P.W. Wilson, Diabetic retinopathy and cardiovascular disease in type II diabetics, The Framingham Heart Study and the Framingham Eye Study, Am J Epidemiol, 128(2) 402-9, 1988.
• R. Klein, B.E. Klein, S.E. Moss, K.J. Cruickshanks, Association of ocular disease and mortality in a diabetic population, Arch Ophthalmol, 117(11) 1487-95, 1999.
• K. Sheng, Shape-directed fundus image scaling method applied on an ophthalmology CAD system, In: Proceedings of Pacific Rim Conference on Communications, Computers and Signal Processing, IEEE 2005 (Eds: F. Gebali, A. Gulliver), pp. 332-335.
• C. Sinthanayothin, J.F. Boyce, H.L. Cook, T.H. Williamsoni, Automated localisation of the optic disc, fovea, and retinal blood vessels from digital color fundus images, Br J Ophthalmol, 83(8) 902–910, 1999.
• T. Walter, J.C. Klein, Segmentation of color fundus images of the human retina: detection of the optic disc and the vascular tree using morphological techniques, Lecture Notes in Computer Science, Volume: 2199, pp: 282-287, 2001.
• A.D. Fleming, K.A. Goatman, S. Philip, J.A. Olson, P.F. Sharp, Automatic detection of retinal anatomy to assist diabetic retinopathy screening, Physics in Medicine and Biology, 52(2) 331-45, 2007.
• P. Treigys, V. Šaltenis, G. Dzemyda, V. Barzdžiukas, A. Paunksnis, Automated optic nerve disc parameterization, Informatica1, 9(3) 403–420, 2008.
• M. Nergiz, S. Ari, M. Akin, Optic disc detection in retinal images via a new algorithm, In: Proceeding of National Congress of Medical Technologies, 74-77, 2014 (in Turkish).
• K. Adem, M. Hekim, S. Demir, Detection of optic disc location in retinal images using image processing techniques, Electric-Electronics and Computer Symposium, 168-171, 2016 (in Turkish).
• A.A.H. Youssif, A.Z. Ghalwash, A.A.S. Abdel-Rahman Ghoneim, Optic disc detection from normalized digital fundus images by means of a vessels direction matched filter, IEEE Trans. Med. Imaging, 27(1) 11–18, 2008.
• H. Cetiner, B. Cetisli, Optical disc detection based on intensity and feature in the retinal images, In: Proceeding of Signal Processing and Communications Applications Congress, 208-211, 2015 (in Turkish).
• T. Kauppi, V. Kalesnykiene, J.K. Kamarainen, L. Lensu, I. Sorri, A. Raninen Voutilainen, R. Uusitalo, H. Kälviäinen, H. Pietilä, DIARETDB1 diabetic retinopathy database and evaluation protocol, Technical report, 2007.
• I. Yilmaz, M. Gullu, T. Baybura, A. O. Erdogan, Color spaces and color transformation program. Afyon Kocatepe University Journal of Science and Engineering, 2(2) 19-35, 2002 (in Turkish).
• C. K. Teo, Digital enhancement of night vision and thermal images. MSc Thesis, Naval Postgraduate School, California, 2003.
• J. Canny, A computational approach to edge detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, 679-700, 1986.
• S. Abdelazeem, Micro-aneurysm detection using vessels removal and circular Hough transform. In: Proceedings of Nineteenth National Radio Science Conference, 421-426, 2002.