Skip to main content
Top
Published in: Journal of Medical Systems 3/2012

01-06-2012 | ORIGINAL PAPER

Automated Identification of Exudates and Optic Disc Based on Inverse Surface Thresholding

Authors: Haniza Yazid, Hamzah Arof, Hazlita Mohd Isa

Published in: Journal of Medical Systems | Issue 3/2012

Login to get access

Abstract

This paper presents a new approach to detect exudates and optic disc from color fundus images based on inverse surface thresholding. The strategy involves the applications of fuzzy c-means clustering, edge detection, otsu thresholding and inverse surface thresholding. The main advantage of the proposed approach is that it does not depend on manually selected parameters that are normally chosen to suit the tested databases. When applied to two sets of databases the proposed method outperforms a method based on watershed segmentation.
Literature
1.
go back to reference Sinthanayothin, C., Boyce, J. F., Cook, H. L., and Wiliamson, T. H., Automated localisation of the optic disc, fovea and retinal blood vessels from digital colour fundus images. Br. J. Ophthalmol. 83:902–910, 1999.CrossRef Sinthanayothin, C., Boyce, J. F., Cook, H. L., and Wiliamson, T. H., Automated localisation of the optic disc, fovea and retinal blood vessels from digital colour fundus images. Br. J. Ophthalmol. 83:902–910, 1999.CrossRef
2.
go back to reference Lu, S., and Lim, J. W., Automatic optic disc detection from retinal images by line operator. IEEE Trans. Biomed. Eng. 58(1):88–94, 2011.CrossRef Lu, S., and Lim, J. W., Automatic optic disc detection from retinal images by line operator. IEEE Trans. Biomed. Eng. 58(1):88–94, 2011.CrossRef
3.
go back to reference Abdel-Ghafar, R. A, Morris, T., Ritchings, T., Wood, T., Detection and characteristic of the optic disc in glaucoma and diabetic retinopathy. In Proc. Medical Image Understanding Analysis Conf, London, UK, 2004. Abdel-Ghafar, R. A, Morris, T., Ritchings, T., Wood, T., Detection and characteristic of the optic disc in glaucoma and diabetic retinopathy. In Proc. Medical Image Understanding Analysis Conf, London, UK, 2004.
4.
go back to reference Osareh, A., Automated identification of diabetic retinal exudates and the optic disc. Ph.D. dissertation, Department of Computer Science, Faculty of Engineering, University of Bristol, Bristol, UK, 2004. Osareh, A., Automated identification of diabetic retinal exudates and the optic disc. Ph.D. dissertation, Department of Computer Science, Faculty of Engineering, University of Bristol, Bristol, UK, 2004.
5.
go back to reference Hoover, A., and Goldbaum, M., Locating optic nerve in a retinal image using the fuzzy convergence of the blood vessels. IEEE Trans. Med. Imag. 22(8):951–958, 2003.CrossRef Hoover, A., and Goldbaum, M., Locating optic nerve in a retinal image using the fuzzy convergence of the blood vessels. IEEE Trans. Med. Imag. 22(8):951–958, 2003.CrossRef
6.
go back to reference Ward, N. P., Tomlinson, S., and Taylor, C. J., Image analysis of fundus photographs - the detection and measurement of exudates associated with diabetic retinopathy. Ophthalmology 96:80–86, 1989. Ward, N. P., Tomlinson, S., and Taylor, C. J., Image analysis of fundus photographs - the detection and measurement of exudates associated with diabetic retinopathy. Ophthalmology 96:80–86, 1989.
7.
go back to reference Philips, R., Forrester, J., and Sharp, P., Automated detection and quantification of retinal exudates. Graefe Arch. Clin. Exp. Ophthalmol. 231(2):90–94, 1994.CrossRef Philips, R., Forrester, J., and Sharp, P., Automated detection and quantification of retinal exudates. Graefe Arch. Clin. Exp. Ophthalmol. 231(2):90–94, 1994.CrossRef
8.
go back to reference Frame, A. J., Undill, P. E., Cree, M. J., Olson, J. A., McHardy, K. C., Sharp, P. F., and Forrester, J. F., A comparison of computer based classification methods applied to the detection of microaneurysms in ophtalmic fluorescein angiograms. Comput. Biol. Med. 28:225–238, 1998.CrossRef Frame, A. J., Undill, P. E., Cree, M. J., Olson, J. A., McHardy, K. C., Sharp, P. F., and Forrester, J. F., A comparison of computer based classification methods applied to the detection of microaneurysms in ophtalmic fluorescein angiograms. Comput. Biol. Med. 28:225–238, 1998.CrossRef
9.
go back to reference Wang, H., Hsu, W., Goh, K. G., and Lee, M. L., An effective approach to detect lesions in color retinal images. Proceedings of IEEE Conference on Computer Vision and Pattern recognition, Hilton Head Island, USA, pp. 181–186, 2000. Wang, H., Hsu, W., Goh, K. G., and Lee, M. L., An effective approach to detect lesions in color retinal images. Proceedings of IEEE Conference on Computer Vision and Pattern recognition, Hilton Head Island, USA, pp. 181–186, 2000.
10.
go back to reference Ege, B. M., Hejlesen, O. K., Larsen, O. V., Moller, K., Jennings, B., Kerr, D., and Cavan, D. A., Screening for diabetic retinopathy using computer based image analysis and statistical classification. Comput. Meth. Programs Biomed. 62(3):165–175, 2000.CrossRef Ege, B. M., Hejlesen, O. K., Larsen, O. V., Moller, K., Jennings, B., Kerr, D., and Cavan, D. A., Screening for diabetic retinopathy using computer based image analysis and statistical classification. Comput. Meth. Programs Biomed. 62(3):165–175, 2000.CrossRef
11.
go back to reference Osareh, A., Mirmehdi, M., Thomas, B., and Markham, R., Automatic recognition of exudative maculopathy using fuzzy c-means clustering and neural networks. In Proc. Medical Image Understanding Analysis Conf., pp. 49–52, July 2001. Osareh, A., Mirmehdi, M., Thomas, B., and Markham, R., Automatic recognition of exudative maculopathy using fuzzy c-means clustering and neural networks. In Proc. Medical Image Understanding Analysis Conf., pp. 49–52, July 2001.
12.
go back to reference Walter, T. J., Klein, C., Massin, P., and Erginay, A., A contribution of image processing to the diagnosis of diabetic retinopathy—detection of exudates in color fundus images of the human retina. IEEE Trans. Med.Imag. 21(10):1236–1243, 2002.CrossRef Walter, T. J., Klein, C., Massin, P., and Erginay, A., A contribution of image processing to the diagnosis of diabetic retinopathy—detection of exudates in color fundus images of the human retina. IEEE Trans. Med.Imag. 21(10):1236–1243, 2002.CrossRef
13.
go back to reference Kevin, N., Nayak, J., Bhat, S. N., Enhancement of retinal fundus Image to highlight the features for detection of abnormal eyes. TENCON 2006. 2006 IEEE Region 10 Conference, pp. 1–4, 2006. Kevin, N., Nayak, J., Bhat, S. N., Enhancement of retinal fundus Image to highlight the features for detection of abnormal eyes. TENCON 2006. 2006 IEEE Region 10 Conference, pp. 1–4, 2006.
14.
go back to reference Li, H., and Chutatape, O., A model-based approach for automated feature extraction in fundus images. ICCV 2003:394–399, 2003. Li, H., and Chutatape, O., A model-based approach for automated feature extraction in fundus images. ICCV 2003:394–399, 2003.
15.
go back to reference Sanchez, C. I., Hornero, R., Lopez, M. I., and Poza, J., Retinal image analysis to detect and quantify lesions associated with diabetic retinopathy. Proc. 26th IEEE Annual International Conf. on Engineering in Medicine and Biology Society (EMBC) 3:1624–1627, 2004. Sanchez, C. I., Hornero, R., Lopez, M. I., and Poza, J., Retinal image analysis to detect and quantify lesions associated with diabetic retinopathy. Proc. 26th IEEE Annual International Conf. on Engineering in Medicine and Biology Society (EMBC) 3:1624–1627, 2004.
16.
go back to reference Chuai-Aree, S., Lursinsap, C., Sophatsathit, P., and Siripant, S., Fuzzy C-mean: A statistical feature classification of text and image segmentation method. Proc. of Intern. Conf. on Intelligent Technology 2000, December 13–15, Assumption University Bangkok, Thailand, pp. 279–284, 2000. Chuai-Aree, S., Lursinsap, C., Sophatsathit, P., and Siripant, S., Fuzzy C-mean: A statistical feature classification of text and image segmentation method. Proc. of Intern. Conf. on Intelligent Technology 2000, December 13–15, Assumption University Bangkok, Thailand, pp. 279–284, 2000.
17.
go back to reference Gonzalez, R. C., and Woods, R. E., Digital image processing. Prentice Hall, Upper Saddle River, 2002. Gonzalez, R. C., and Woods, R. E., Digital image processing. Prentice Hall, Upper Saddle River, 2002.
18.
go back to reference Otsu, N., A threshold selection method from gray-level histogram. IEEE Trans. Syst. Man Cybern. 9(1):62–66, 1979.MathSciNetCrossRef Otsu, N., A threshold selection method from gray-level histogram. IEEE Trans. Syst. Man Cybern. 9(1):62–66, 1979.MathSciNetCrossRef
19.
go back to reference Reza, A. W., Eswaran, C., and Hati, S., Automatic tracing of optic disc and exudates from color fundus images using fixed and variable threshold. J. Med. Syst. 33:73–80, 2009.CrossRef Reza, A. W., Eswaran, C., and Hati, S., Automatic tracing of optic disc and exudates from color fundus images using fixed and variable threshold. J. Med. Syst. 33:73–80, 2009.CrossRef
Metadata
Title
Automated Identification of Exudates and Optic Disc Based on Inverse Surface Thresholding
Authors
Haniza Yazid
Hamzah Arof
Hazlita Mohd Isa
Publication date
01-06-2012
Publisher
Springer US
Published in
Journal of Medical Systems / Issue 3/2012
Print ISSN: 0148-5598
Electronic ISSN: 1573-689X
DOI
https://doi.org/10.1007/s10916-011-9659-4

Other articles of this Issue 3/2012

Journal of Medical Systems 3/2012 Go to the issue