Abstract
Glaucoma is a leading cause of blindness worldwide, accounting for 12.3% of the permanently blind according to the World Heath Organization. The disease is particularly prevalent in Asia, with up to 50% of total glaucoma cases found in the region. Although glaucomatous damage is irreversible, studies have shown that early detection can be effective in slowing or halting glaucomatous atrophy. The ratio of the size of the optic cup to the optic disc, also known as the cup-to-disc ratio (CDR), is an important indicator for glaucoma assessment, since glaucomatous progression corresponds to increased excavation of the optic cup. In current clinical practice, the CDR is measured manually and can be subjective, limiting its use in screening for early detection. We describe the ARGALI system which automatically calculates the CDR from non-stereographic retinal fundus photographs, providing a fast, objective and consistent measurement. The ARGALI system consists of a series of steps. As the optic disc occupies only a small region of the entire retinal image, a region of interest is first extracted via pixel intensity analysis. Variational level-set algorithm is next used to segment the optic disc. Optic cup segmentation is more challenging due to the cup’s interweavement with blood vessels and surrounding tissues. A multi-modal approach consisting of different methods is used extract the cup. To obtain a smoother contour, ellipse fitting is applied to the extracted cup and disc. A neural network has also been proposed to fuse the results obtained via the various modes. The ARGALI system was tested using images collected from patients at the Singapore Eye Research Institute and achieves an RMS error of 0.05 with a risk assessment accuracy of 95%. The results are promising for ARGALI to be developed into a low cost, objective and efficient screening system for automatic assessment glaucoma risk assessment.
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References
World Health Organisation: Magnitude and Causes of Visual Impairment, http://www.who.int/mediacentre/factsheets/fs282/en/index.html, 2002
Foster P. J., Oen F. T. S., Machine D., Ng T.-P., Devereux J. G., Johnson G. J., Khaw P. T., and Seah S. K. L. (2000). The Prevalence of Glaucoma in Chinese Residents of Singapore: A Cross-Sectional Population Survey of the Tanjong Pagar District. Arch Ophthalmol, vol. 118, pp. 1105–1111, August 2000.
Li H., Chutatape O. (2003) A model-based approach for automated feature extraction in fundus images. In Proc. of the 9th IEEE International Conference on Computer Vision, Nice, France, 2003.
Tang Y., Li X., Freyberg A., Goch G. (2006) Automatic segmentation of the papilla in a fundus image based on the C-V model and a shape restraint. In Proc. of the 18th International Conference on Pattern Recognition, Hong Kong, 2006.
Inoue N., Yanashima K., Magatani K., Kurihara K. (2005) Development of a simple diagnostic method for the glaucoma using ocular fundus pictures. In Proc. of the 27th IEEE engineering in medicine and biology annual conference, Shanghai, China, 2005.
Xu J., Chutatape O., Sung E., Zheng C., Kuan P. C. T. (2007). Optic disk feature extraction via modified deformable model technique for glaucoma analysis. Pattern Recognition 40 2063–2076, 2007.
Li C., Xu, C., Gui C., Fox M. D. (2005) Level set evolution without re-initialization: a new variational formulation. In Proc. of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, USA, 2005.
Liu J., Wong D.W.K., Lim J.H., Li H., Jia X., Yin F., Xiong W. (2008). Optic Cup and Disk Extraction from Retinal Fundus Images for Determination of Cup-to-Disc Ratio. IEEE Conference on Industrial Electronics and Applications. Singapore, 2008.
Fitzgibbon A., Pilu M., Fisher R. B.. Direct least-squares fitting of ellipses. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(5), 476–480, May 1999.
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© 2009 International Federation of Medical and Biological Engineering
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Liu, J. et al. (2009). ARGALI: An Automatic Cup-to-Disc Ratio Measurement System for Glaucoma Analysis Using Level-set Image Processing. In: Lim, C.T., Goh, J.C.H. (eds) 13th International Conference on Biomedical Engineering. IFMBE Proceedings, vol 23. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92841-6_137
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DOI: https://doi.org/10.1007/978-3-540-92841-6_137
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