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Sensors 2009, 9(3), 2148-2161; doi:10.3390/s90302148
Article

Automatic Exudate Detection from Non-dilated Diabetic Retinopathy Retinal Images Using Fuzzy C-means Clustering

1,* , 1
 and
2
1 Department of Information Technology, Sirindhorn International Institute of Technology, Thammasat University 131 Moo 5, Tiwanont Road, Bangkadi, Muang, Pathumthani 12000, Thailand 2 Faculty of Computing, Information Systems and Mathematics, Kingston University Penrhyn Road, Kingston upon Thames, Surrey, KT1 2EE, UK
* Author to whom correspondence should be addressed.
Received: 29 January 2009 / Revised: 19 March 2009 / Accepted: 20 March 2009 / Published: 24 March 2009
(This article belongs to the Section Physical Sensors)
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Abstract

Exudates are the primary sign of Diabetic Retinopathy. Early detection can potentially reduce the risk of blindness. An automatic method to detect exudates from low-contrast digital images of retinopathy patients with non-dilated pupils using a Fuzzy C-Means (FCM) clustering is proposed. Contrast enhancement preprocessing is applied before four features, namely intensity, standard deviation on intensity, hue and a number of edge pixels, are extracted to supply as input parameters to coarse segmentation using FCM clustering method. The first result is then fine-tuned with morphological techniques. The detection results are validated by comparing with expert ophthalmologists’ hand-drawn ground-truths. Sensitivity, specificity, positive predictive value (PPV), positive likelihood ratio (PLR) and accuracy are used to evaluate overall performance. It is found that the proposed method detects exudates successfully with sensitivity, specificity, PPV, PLR and accuracy of 87.28%, 99.24%, 42.77%, 224.26 and 99.11%, respectively.
Keywords: exudates; diabetic retinopathy; non-dilated retinal images; Fuzzy C-Means clustering exudates; diabetic retinopathy; non-dilated retinal images; Fuzzy C-Means clustering
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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Sopharak, A.; Uyyanonvara, B.; Barman, S. Automatic Exudate Detection from Non-dilated Diabetic Retinopathy Retinal Images Using Fuzzy C-means Clustering. Sensors 2009, 9, 2148-2161.

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