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Automated Diagnosis Non-proliferative Diabetic Retinopathy in Fundus Images using Support Vector Machine

by Raju Sahebrao Maher, Sangramsing N. Kayte, Sandip T. Meldhe, Mukta Dhopeshwarkar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 125 - Number 15
Year of Publication: 2015
Authors: Raju Sahebrao Maher, Sangramsing N. Kayte, Sandip T. Meldhe, Mukta Dhopeshwarkar
10.5120/ijca2015905968

Raju Sahebrao Maher, Sangramsing N. Kayte, Sandip T. Meldhe, Mukta Dhopeshwarkar . Automated Diagnosis Non-proliferative Diabetic Retinopathy in Fundus Images using Support Vector Machine. International Journal of Computer Applications. 125, 15 ( September 2015), 7-10. DOI=10.5120/ijca2015905968

@article{ 10.5120/ijca2015905968,
author = { Raju Sahebrao Maher, Sangramsing N. Kayte, Sandip T. Meldhe, Mukta Dhopeshwarkar },
title = { Automated Diagnosis Non-proliferative Diabetic Retinopathy in Fundus Images using Support Vector Machine },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 125 },
number = { 15 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 7-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume125/number15/22506-2015905968/ },
doi = { 10.5120/ijca2015905968 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:16:10.708959+05:30
%A Raju Sahebrao Maher
%A Sangramsing N. Kayte
%A Sandip T. Meldhe
%A Mukta Dhopeshwarkar
%T Automated Diagnosis Non-proliferative Diabetic Retinopathy in Fundus Images using Support Vector Machine
%J International Journal of Computer Applications
%@ 0975-8887
%V 125
%N 15
%P 7-10
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Diabetic retinopathy (DR) is caused by damage the retina because fluid leaks from blood vessels into the retina. Damage the posterior part of the eye of the diabetic patient. This disease that occurs when does not secrete enough insulin or the body is unable to process it properly. The main two types of diabetic retinopathy the first are non-proliferate diabetes retinopathy (NPDR) and second are proliferate diabetes retinopathy (PDR). The increasing number of DR cases world-wide demands to the development of an automated detection system. We have proposed a computer based method for the detection of diabetic retinopathy using the fundus images. Using Image pre-processing, morphological processing techniques involves processing of fundus images for detect features, such as blood vessel area, exudates, microaneurysms, hemorrhages, and texture. Proposed techniques used for the extraction of these features from digital fundus images. The proposed techniques have been tested on the images of DIARETDB0 database. In which have total 130 images they all images are tested and it’s classified into microaneurysms, hemorrhages, and texture using Support Vector Machine (SVM) for an automatic classification. The detection results obtained by comparing it with expert ophthalmologists. We demonstrated a classification sensitivity of 96.43%, specificity of 95.9 % and accuracy of 99.27 %.

References
  1. World Diabetes, A newsletter from the World Health Organization, 4, 1998.
  2. Ong, G. L., Ripley, L. G., Newsom, R. S., Cooper, M., and Casswell, A. G., Screening for sight-threatening diabetic retinopathy: comparison of fundus photography with automated color contrast threshold test. Am. J. Ophthalmol. 137(3):445–452, 2004.
  3. Orbis. Retrieved from: http://www.orbis. org. Last accessed December 2009.
  4. Alberti, K. G., and Zimmet, P. Z., 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. 15(7):539–553, 1998.
  5. UK Prospective Diabetes Study Group: Tight blood pressure control and risk of macrovascular and microvascular complications in type 2 diabetes: UKPDS 38.BMJ 317: 708–713, 1998.
  6. Wong, L. Y., Acharya, U. R., Venkatesh, Y. V., Chee, C., Lim, C. M., and Ng, E. Y. K., Identification of different stages of diabetic retinopathy using retinal optical images. Information Sciences 178(1):106–121, 2008.
  7. . Adarsh. P and D. Jeyakumari, Multiclass SVM-Based Automated Diagnosis of Diabetic Retinopathy International conference on Communication and Signal Processing, April 3-5, 2013, India.
  8. 26.Kauppi, T., Kalesnykiene, V., Kamarainen, J. K., Lensu, L., Sorri, I., Uusitalo, H., Kälviäinen, H., Pietilä, J., DIARETDB0: Evaluation database and methodology for diabetic retinopathy algorithms. Technical Report, 2006.
  9. Kauppi, T., Kalesnykiene, V., Kamarainen, J.-K., Lensu, L., Sorri, I., Raninen A., Voutilainen R., Uusitalo, H., Kälviäinen, H., Pietilä, J., DIARETDB1 diabetic retinopathy database and evaluation protocol, Technical report, 2007.
  10. Walter, T., Klein, J.-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.
  11. Reza, A. W., Eswaran, C., and Hati, S., Automatic tracing of optic disc and exudates from color fundus images using fixed and variable thresholds. J. Med. Syst. 33 (1)73–80, 2009.
  12. Raju Maher, Sangramsing Kayte, Dr. Mukta Dhopeshwarkar "Review of Automated Detection for Diabetes Retinopathy Using Fundus Images" International Journal of Advanced Research in Computer Science and Software Engineering Volume 5, Issue 3, March 2015
Index Terms

Computer Science
Information Sciences

Keywords

Diabetic Retinopathy Fundus images Microaneurysms Exudates Retinal blood vessels. Image morphology artificial neural network.