Detection of Diabetic Retinopathy from Fundus Camera Images

Sheeba O; Ajitha S. S.

doi:https://doi.org/10.14445/22315381/IJETT-V24P233

Research Article | Open Access | Download PDF

Volume 24 | Number 1 | Year 2015 | Article Id. IJETT-V24P233 | DOI : https://doi.org/10.14445/22315381/IJETT-V24P233

Detection of Diabetic Retinopathy from Fundus Camera Images

Sheeba O, Ajitha S. S.

Citation :

Sheeba O, Ajitha S. S., "Detection of Diabetic Retinopathy from Fundus Camera Images," International Journal of Engineering Trends and Technology (IJETT), vol. 24, no. 1, pp. 177-181, 2015. Crossref, https://doi.org/10.14445/22315381/IJETT-V24P233

Abstract

Diabetic Retinopathy is the major cause of adult blindness. We can prevent loss of vision if the disease is identified in the early stage itself. Also early detection of the disease is essential for preventing the progress of the disease. Examination of retinal vessels is the first step towards detection of the disease. Moreover segmentation of retinal vasculature helps in the diagnosis of many diseases like Hypertension, Arteriosclerosis etc. This paper presents segmentation of retinal vasculature by Gabor wavelet feature based kernel classifier (Support Vector Machine) and its use for detection of early symptoms of Diabetic Retinopathy. Performance evaluation is conducted using publicly available database DRIVE with reference to the manually segmented images given in the database. The performance of the classifiers are evaluated in terms of accuracy, sensitivity, specificity.

Keywords

Retina, Diabetic Retinopathy, Gabor Wavelet, Support Vector Machine.

References

[1] Huiqi Li and OpasChutatape, “Fundus Image Feature Extraction”, Proceedings of the 22nd annual EMBS Conference, uly 23-28, 2000, Chicago IL.
[2] Ana Maria Mendonça, and Aurelio Campilho, “Segmentation of Retinal Blood Vessels by Combining the Detection of Centerlines and Morphological Reconstruction”, IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 25, NO. 9, SEPTEMBER 2006.
[3] DivyanjaliSatyarthi, B.A.N. Raju, and S. Dandapat, “Detection of Diabetic Retinopathy in Fundus Images using Vector Quantization Technique”, 1-4244-0370-7/06/2006 IEEE.
[4] R.Ghaderi, H.Hassanpour, M.Shahiri, “Retinal Vessel Segmentation Using the 2-D Morlet Wavelet and Neural Network”, International Conference on Intelligent and Advanced Systems 2007.
[5] Yong Yang, Shuying Huang, NiniRao, “An Automatic Hybrid Methodfor Retinal Blood Vessel Extraction”, Int. J. Appl. Math. Comput. Sci., 2008, Vol. 18, No. 3, 399–407.
[6] M. ShahramMoin, HamedRezazadeganTavy akoli, Ali Broumandnia, “A New Retinal Vessel Segmentation Method Using Preprocessed Gabor and Local Binary Patterns”, 2010 IEEE.
[7] Seyed Mohsen Zabihi, MortezaDelgir, and Hamid Reza Pourreza, “Retinal Vessel Segmentation Using Color Image Morphology and Local Binary Patterns”, Machine Vision and Image Processing (MVIP).
[8] Simon Haykins, “Neural Networks – A Comprehensive Foundation
[9] V. Vijayakumari, N. Suriyanarayanan, C. Thanka Saranya, “Feature Extraction for Early Detection of Diabetic Retinopathy ”, Internationa Conference on Recent trends in Information, Telecommunication and Computing.