Detection of Glaucoma using Cup-to-Disc Ratio and Blood Vessels Orientation

Authors

  • Deepthi K Prasad  Full Time Research Scholar, Department of CSE, B N M Institute of Technology, Bangalore, Karnataka, India
  • Vibha L  Professor, Department of CSE, B N M Institute of Technology, Bangalore, Karnataka, India
  • Venugopal K R  Principal, UVCE, Bangalore University, Bangalore, Karnataka, India

Keywords:

Glaucoma, Optic Cup, Optic Disc, Cup-To-Disc Ratio, Fundus Images, Blood Vessels

Abstract

Glaucoma is a disorder of that result in the injury to the optic nerve of the eye due to increased in the Intra Ocular Pressure (IOP). It can damage the optic nerve asymptotically, lead to vision impairment and progress into permanent blindness if it is not treated early. In the proposed work, the presence of glaucoma is detected by analysing the fundus images. The work includes method for segmentation of the retinal optic cup (OC) and the disc. The size and shape of the optic cup are measured. The Cup-to-Disc Ratio (CDR) is computed. The blood vessels present inside the optic disc (OD) are also segmented and their orientation is analysed which strengthens the accuracy of the detection. The input images are classified as glaucomatous or normal based on the combined results of CDR and blood vessel orientation. DRIONS database images are used to carry out the experimentation, the outcomes are optimistic. The accuracy obtained is 96%.

References

  1. PrJun Cheng, Fengshou yin, Damon wong, " Sparse Dissimilarity Constrained Coding for Glaucoma Screening", IEEE transactions on biomedical engineering, vol 62,No. 5,May 2015.
  2. Jiang liu, yan wu, "Super pixel classification based segmentation of OD and optic cup" , IEEE transaction on medical imaging, June 2013.
  3. Prashanth, arun kumar patil, Ravi Shankar mishra, "Segmenting the Optic Disc in Retinal images using Adaptive Thresholding", International Journal of Computer Applications (0975 – 8887), May 2014.
  4. Singh A., Dutta M. K., ParthaSarathi M., Uher V., Burget R, "Image processing based automatic diagnosis of glaucoma using wavelet features of segmented optic disc from fundus image", Computer Methods and Programs in Biomedicine. 2016; 124:108–120. doi: 10.1016/j.cmpb.2015.10.010. (0975 – 8887), Aug 2015.
  5. Li and Chutatape, "An adaptive threshold based image processing technique", International Journal of Computer Applications (0975 – 8887), April 2014.
  6. A. K. Nandi, W. Al. Nuaimy and S. Sekhar, "Automated Localisation of an Optical Disk and Fovea in Retinal Images", 16th European Signal Processing Conference (EUSIPCO 2008), Lausanne, Switzerland, August 25-29, 2008
  7. Sakthivel K, Narayanan R. "An automated detection of glaucoma using histogram features", International Journal of Ophthalmology, pp.194-200, 2015,  doi:10.3980/j.issn.2222-3959.2015.01.33.
  8. Pachiyappan, A., Das, U., Murthy, T., Tatavarti, R. "Automated diagnosis of diabetic retinopathy and glaucoma using fundus and OCT images", Lipids Health Dis. 11(1), 73, 2012
  9. K. Kavitha, M. Malathi, "Optic Disc and Optic Cup Segmentation for Glaucoma Classification", International Journal of Advanced Research in Computer Science& Technology (IJARCST 2014), vol. 2, Jan-March 2014.
  10. S. Letishia Mary, "Segmenting Optic Disk Cup in Retinal Fundus Images", International Journal of Computer Applications (0975–8887) International Seminar on Computer Vision (ISCV-2013).
  11. E.J. Carmona, M. Rincón, J. García-Feijoo and J. M. Martínez-de-la-Casa, "Identification of the optic nerve head with genetic algorithms", Artificial Intelligence in Medicine, Vol. 43(3), pp. 243-25, 2008.

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Published

2018-02-28

Issue

Section

Research Articles

How to Cite

[1]
Deepthi K Prasad, Vibha L, Venugopal K R, " Detection of Glaucoma using Cup-to-Disc Ratio and Blood Vessels Orientation , IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.1515-1520, January-February-2018.