Abstract
Glaucoma, an eye disease recognized to be the second most leading cause of blindness worldwide. Early detection and subsequent treatment of glaucoma is hence important as damage done by glaucoma is irreversible. Large scale manual screening of glaucoma is a challenging task as skilled manpower in ophthalmology is low. Hence many works have been done towards automated glaucoma detection system from the color fundus images (CFI). In this paper, we propose a novel method of automated glaucoma detection from CFI using color channel adaptive thresholding and ISNT rule. Structural features such as cup-to-disk ratio (CDR), neuro-retinal rim (NRR) area of the optic nerve head (ONH) are extracted from CFI using color channel adaptive thresholding and morphological processing in order to segment Optic Disk (OD) and Optic Cup (OC) required for calculating the CDR value. The results obtained by the proposed methodology are very promising yielding an overall efficiency of 99%.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Glaucoma Research Foundation. http://www.glaucoma.org/glaucoma/typesofglaucoma.php
Quigley, H.A., Broman, A.T.: The number of people with glaucoma worldwide in 2010 and 2020. Brit. J. Ophthalmol. 90(3), 262–267 (2006)
Inoue, N., Yanashima, K., Magatani, K., Kurihara, T.: Development of a simple diagnostic method for the glaucoma using ocular fundus pictures. In: Proceedings of 2005 IEEE, Engineering in Medicine and Biology 27th Annual Conference, pp. 3355–3358. Shanghai, China (2006)
Hatanaka, Y., Noudo, A., Muramatsu, C., Sawada, A., Hara, T., Yamamoto, T., Fujita, H.: Automatic measurement of cup to disc ratio based on line profile analysis in retinal images. Conf Proc IEEE Eng Med Bioi Soc. (2011)
Narasimhan, K., Vijayarekha, K.: An efficient automated system for glaucoma detection using fundus image. J. Theor. Appl. Inf. Technol. 33, 104–110 (2011). E-ISSN: 1817- 3195
Kavitha, S., Karthikeyan, S., Duraiswamy, K.: Early detection of glaucoma in retinal image using cup to disc ratio. In: Second International Conference on Computing, Communication and Networking Technologies, vol 10, IEEE (2010)
Joshi, G., Sivaswamy, J., Karan, K., Prashanth, R., Krishnadas, S.R.: Vessel bend-based cup segmentation in retinal images. In: 20th International Conference on Pattern Recognition(ICPR), pp. 2536–2539. (2010)
Joshi, G.: Sivaswamy, Krishnadas S.R.: Optic disk and cup segmentation from monocular retinal images for glaucoma assessment. IEEE Trans. Med. Imaging 30, 1192–1205 (2011)
Murthi, A., Madheswaran, M.: Enhancement of optic cup to disc ratio detection in glaucoma diagnosis, In: International Conference on Computer Communication and Informatics (ICCCI), pp. 1–5. IEEE (2012)
Joshi, G., Sivaswamy, J., Krishnadas, S.R.: Depth discontinuity-based cup segmentation from multi-view colour retinal images. IEEE Trans. Biomed. Eng. 59, 1523–1531 (2012)
Ahmad, H., Yamin, A., Shakeel, A., Gillani, S.O., Ansari, U.: Detection of glaucoma using retinal fundus images. In: International Conference on Robotics and Emerging Allied Technologies in Engineering (iCREATE), pp. 321–324. IEEE (2014)
Alghmdi, H., Tang, H.L., Hansen, M., O’Shea, A., Al Turk, L., Peto, T.: Measurement of optical cup-to-disc ratio in fundus images for glaucoma screening. In: International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM), pp. 1–5. IEEE (2015)
Vijapur, N.A., Kunte, R.S.R.: Glaucoma detection by using Pearson-R correlation filter. In: International Conference on Communications and Signal Processing (ICCSP), pp. 1194–1198. IEEE (2015)
Shekhar, S., Al-Nuaimy, W., Nandi, A.K.: Automated Localization of Retinal Optic Disk Using Hough Transform. IEEE, ISBI, pp. 1577–1580 (2008)
Yin, F., Liu, J., Wong, D.W.K., Tan, N.M., Cheung, C., Bhaskaran, M., Wong, T.Y.: Automated segmentation of optic disk and optic cup in fundus images for glaucoma diagnosis. In: 25th International Symposium on Computer Based Medical System, pp. 1–6 (2012)
Aquino, A., Gegundez-Arias, M.E., Marin, D.: Detecting the optic disk boundary in digital fundus images using morphological, edge detection and feature extraction techniques. IEEE Trans. Med. Imaging 29, 1860–1869 (2010)
Liu, J., Wong, D., Lim, J., Li, H., Tan, N., Wong, T.: Argali-an automatic cup-to-disc ratio measurement system for glaucoma detection and analysis framework. In: Proceeding of SPIE Medical Imaging, vol. 7260, p. 72603 K. (2009)
Joshi, G.D., Sivaswamy, J., Karan, K., Krishnadas, R.: Optic disk and cup boundary detection using regional information. In: Proceeding of IEEE International Symposium on Biomedical Imaging (ISBI), pp. 948–951 (2010)
Sivaswamy, J., Krishnadas, S.R., Chakravarty, A., Joshi, G.D., Ujjwal, et al.: A Comprehensive retinal image dataset for the assessment of glaucoma from the optic nerve head analysis. JSM Biomed. Imaging Data Pap. 2(1), 1004 (2015)
Acknowledgements
We would like to express our sincere gratitude and deep regard to Poojya Dr. Sharnbaswappa Appaji, President, Sharanabasveshwar Vidya Vardhaka Sangha, Kalaburagi, for his immense support and encouragement. We would also like to give our sincere gratitude to Dr. V.D Mytri, Principal, APPA IET, Dr. Anilkumar Bidve, Dean of Administration, APPA IET for their invaluable suggestions and support. We thank Dr. Pradeep Reddy, Dr. Rohit Patil for providing us the clinical insights of glaucoma.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Nawaldgi, S., Lalitha, Y.S., Reddy, M. (2018). A Novel Adaptive Threshold and ISNT Rule Based Automatic Glaucoma Detection from Color Fundus Images. In: Satapathy, S., Bhateja, V., Raju, K., Janakiramaiah, B. (eds) Data Engineering and Intelligent Computing. Advances in Intelligent Systems and Computing, vol 542 . Springer, Singapore. https://doi.org/10.1007/978-981-10-3223-3_13
Download citation
DOI: https://doi.org/10.1007/978-981-10-3223-3_13
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-3222-6
Online ISBN: 978-981-10-3223-3
eBook Packages: EngineeringEngineering (R0)