Detection of Optic Disc Centre Point in Retinal Image

Latifah Listyalina, Dhimas Arief Dharmawan

Abstract


Glaucoma and diabetic retinopathy (DR) are the two most common retinal related diseases occurred in the world. Glaucoma can be diagnosed by measuring optic cup to disc ratio (CDR) defined as optic cup to optic disc vertical diameter ratio of retinal fundus image. A computer based optic disc is expected to assist the ophthalmologist to find their location which are necessary for glaucoma and DR diagnosis. However, many optic disc detection algorithms available now are commonly non-automatic and only work in healthy retinal image. Therefore, there is not information on how optic disc in retinal image of unhealthy patient can be extracted computationally. In this research work, the method for automated detection of optic disc on retinal colour fundus images has been developed to facilitate and assist ophthalmologists in the diagnosis of retinal related diseases. The results indicated that the proposed method can be implemented in computer aided diagnosis of glaucoma and diabetic retinopathy system development.

Full Text:

PDF

References


Z. Zhang, H. Lee, J. Liu, W. K. Wong, N. M. Tan, and J. Hwee, “Optic Disc Region of Interest Localization in Fundus Image for Glaucoma Detection in ARGALI,” Conference on Industrial Electronics and Applicationsis, pp. 1686–1689, 2010

M. K. Dutta and A. K. Mourya, “Glaucoma Detection by Segmenting the Super Pixels from Fundus Colour Retinal Images,” International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom), pp. 86–90, 2014.

A. P. Shibal Bhartiya, Ritu Gadia, Harinder S Sethi, “Clinical Evaluation of Optic Nerve Head in Glaucoma,” Clinical Evaluation of Optic Nerve Head in Glaucoma, vol. vol. 92, pp. 115–132, 2010

R. Odstrcilik, Jan. Kolar, “Analysis of Retinal Image Data To Support Glaucoma Diagnosis,” ÚSTAV BIOMEDICÍNSKÉHO INŽENÝRSTVÍ, 2014.

P. K. Kohli, “Exact Detection of Optic Disc in Retinal Images using

Segemntation based on Level Set Method and Morphology Operations,”

Thapar University, Patiala, pp. 1–59, 2012.

H. A. Nugroho, L. Listyalina, N. A. Setiawan, S. Wibirama, and D. A. Dharmawan, “Automated Segmentation of Optic Disc Area using

Mathematical Morphology and Active Contour,” International

conference on computer, control, informatics, and its applications, pp.

–22, 2015.

M. Zubair, “Automated Detection of Optic Disc for the Analysis of

Retina Using Color Fundus Image,” IEEE Int. Conf. Imaging Syst. Tech,

pp. 239 – 242, 2013.

P. Choukikar, A. K. Patel, and R. S. Mishra, “Segmenting the Optic Disc in Retinal Images Using Bi- Histogram Equalization and Thresholding the Connected Regions,” International Journal of Emerging Technology and Advanced Engineering, vol. 4, no. 6, 2014.

V. M. Mane and D. V. Jadhav, “Review: Progress Towards Automated Early Stage Detection of Diabetic Retinopathy: Image Analysis Systems and Potential,” Journal of Medical and Biological Engineering, vol. 34, 2014.

I. D. Federation, “Diabetes : Facts and Figures,” Diabetes, p. 3, 2014.

P. Z. Alberti, K. G., and Zimmet, “Definition, diagnosis and classification of diabetes mellitus and its complications, part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation,” Diabet. Med., pp. 15(7):539–553, 1998.

J. S. Kaur, “Automated Localisation of Optic Disc and Macula from

Fundus Images,” International Journal of Advanced Research in Computer Science and Software Engineering, vol. 2, no. 4, pp. 242–249,

M. U. Akram, A. Khan, K. Iqbal, and W. H. Butt, “Retinal Images : Optic Disk Localization,” International Conference on Image Analysis and Recognition, pp. 40–49, 2010.

G. D. Joshi, J. Sivaswamy, and S. R. Krishnadas, “Optic Disk and Cup Segmentation From Monocular Color Retinal Images for Glaucoma

Assessment,” IEEE Transactions on Medical Imaging, vol. 30, no. 6, pp.

–1205, 2011.

Lee Ann Ramington, Clinical Anatomy and Physiology of The Visual System, no. 1. 2014.

P. Gosh, Collier. Varikarra, “Fundoscopy Made Easy: The Normal

Fundus and Its Variants,” Churchill Livingstone, Elsevier, p. 21, 2010.

Glaucoma NZ to safe sight, “Your Glaucoma Eye Examination : Part 2 Your Optic Disc,” Glaucoma, vol. 5, no. 2, pp. 8–9, 2015.

M. P. Waghmare, S. D. Chede, and P. S. M. Sakhare, “Design Strategies for Classification of Abnormalities in Retinal Images Using ANFIS,” International Journal of Application or Innovation in Engineering & Management, vol. 3, no. 3, pp. 388–393, 2014.

M. Sahebrao, Raju. N, Sangramsing. Meldhe, Sandip T. Dhopeshwarkar, “Automated Diagnosis Non-proliferative Diabetic Retinopathy in Fundus Images using Support Vector Machine,” International Journal of Computer Applications, vol. 125, no. 15, pp. 7–10, 2015.

K. J. Zana F, “A Multi-Modal Registration Algorithm of Eye Fundus

Images Using Vessels Detection and Hough Transform,” IEEE transactions on medical engineering, vol. vol. 18 no, pp. 419–428, 1999.

Automated localisation of optic disc in retinal colour fundus image for assisting in the diagnosis of glaucoma. L Listyalina, HA Nugroho, S Wibirama, WKZ Oktoeberza. Communications in Science and Technology 2 (1)




DOI: https://doi.org/10.18196/jet.3150

Refbacks

  • There are currently no refbacks.


Copyright (c) 2019 Journal of Electrical Technology UMY

 

Office Address:

Journal of Electrical Technology UMY

Department of Electrical Engineering, Universitas Muhammadiyah Yogyakarta

Jl. Brawijaya, Kasihan, Bantul, Daerah Istimewa Yogyakarta

Phone/Fax: +62274-387656/ +62274-387646,

E-mail: jet@umy.university

Creative Commons License
Journal of Electrical Technology UMY is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.