Detection of Diabetic Retinopathy from Fundus Camera Images
Citation
Sheeba O, Ajitha S. S."Detection of Diabetic Retinopathy from Fundus Camera Images", International Journal of Engineering Trends and Technology (IJETT), V24(4),177-181 June 2015. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
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.
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.
Keywords
Retina, Diabetic Retinopathy, Gabor Wavelet,
Support Vector Machine.