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Study on Diabetic Retinopathy Detection Techniques

K.K. Faisal1 , C.M. Deepa2 , S.M. Nisha3 , G. Gopi4

Section:Survey Paper, Product Type: Journal Paper
Volume-4 , Issue-11 , Page no. 137-140, Nov-2016

Online published on Nov 29, 2016

Copyright © K.K. Faisal , C.M. Deepa, S.M. Nisha, G. Gopi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: K.K. Faisal , C.M. Deepa, S.M. Nisha, G. Gopi, “Study on Diabetic Retinopathy Detection Techniques,” International Journal of Computer Sciences and Engineering, Vol.4, Issue.11, pp.137-140, 2016.

MLA Style Citation: K.K. Faisal , C.M. Deepa, S.M. Nisha, G. Gopi "Study on Diabetic Retinopathy Detection Techniques." International Journal of Computer Sciences and Engineering 4.11 (2016): 137-140.

APA Style Citation: K.K. Faisal , C.M. Deepa, S.M. Nisha, G. Gopi, (2016). Study on Diabetic Retinopathy Detection Techniques. International Journal of Computer Sciences and Engineering, 4(11), 137-140.

BibTex Style Citation:
@article{Faisal_2016,
author = {K.K. Faisal , C.M. Deepa, S.M. Nisha, G. Gopi},
title = {Study on Diabetic Retinopathy Detection Techniques},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {11 2016},
volume = {4},
Issue = {11},
month = {11},
year = {2016},
issn = {2347-2693},
pages = {137-140},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1122},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1122
TI - Study on Diabetic Retinopathy Detection Techniques
T2 - International Journal of Computer Sciences and Engineering
AU - K.K. Faisal , C.M. Deepa, S.M. Nisha, G. Gopi
PY - 2016
DA - 2016/11/29
PB - IJCSE, Indore, INDIA
SP - 137-140
IS - 11
VL - 4
SN - 2347-2693
ER -

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Abstract

Diabetic Retinopathy (DR) also known as diabetic eye disease. It is the damage occurs to the retina due to diabetes. It can eventually lead to blindness. So the early detection of disease is needed, Manual detection is time consuming and often make observation error. Hence several computer-aided systems are introduced and which would make fast and consistent diagnosis- aid useful for biomedical and health informatics field. The Diabetic retinopathy detection methods that uses machine learning techniques. In one system classifiers such as the Gaussian Mixture model (GMM), k-nearest neighbor (kNN), support vector machine (SVM) are used and another system that uses GMM, kNN, SVM, and combinational classifiers are used for classifying retinal fundus images.

Key-Words / Index Term

Diabetic Retinopathy, Image processing, Feature extraction, Bright lesions, classification, diabetic retinopathy (DR), red lesions, segmentation

References

[1] American Diabetes Association. (2011, Jan. 26). Data from the 2011 national diabetes fact sheet. [Online]. Available: http://www.diabetes.org/diabetes-basics/diabetes-statistics/
[2] S. Roychowdhury, D. D. Koozekanani, and K. K. Parhi, �DREAM: Diabetic Retinopathy Analysis using machine learning,� Biomedical and Health Informatics, IEEE Journal of, vol. 18, no. 5, pp.1717-1728, 2014.
[3] S. Roychowdhury, D. D. Koozekanani, and K. K. Parhi, �Screening fundus images for diabetic retinopathy,� in Proc. Conf. Record 46th Asilomar Conf. Signals, Syst. Comput., 2012, pp. 1641�1645.
[4] L. Shen and L. Bai, �Abstract adaboost gabor feature selection for classification,� in Proc. Image Vis. Comput., 2004, New Zealand, pp. 77�83.
[5] Anitha L. and Arunvinodh C., "Diverse Frameworks on Retina Verification", International Journal of Computer Sciences and Engineering, Volume-02, Issue-12, Page No (62-67), Dec -2014, E-ISSN: 2347-2693.