Automatic Detection of Blood Vessels in Retinal Images for Diabetic Retinopathy Diagnosis
Diabetic retinopathy (DR) is a leading cause of vision loss in diabetic patients. DR is mainly caused due to the damage of retinal blood vessels in the diabetic patients. It is essential to detect and segment the retinal blood vessels for DR detection and diagnosis, which prevents earlier vision los...
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2015-01-01
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Series: | Computational and Mathematical Methods in Medicine |
Online Access: | http://dx.doi.org/10.1155/2015/419279 |
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doaj-d906de6558aa4bcf8e2a4e563d16e8a42020-11-24T22:10:29ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182015-01-01201510.1155/2015/419279419279Automatic Detection of Blood Vessels in Retinal Images for Diabetic Retinopathy DiagnosisD. Siva Sundhara Raja0S. Vasuki1Department of ECE, SACS MAVMM Engineering College, Madurai, Tamil Nadu 625 301, IndiaDepartment of ECE, Velammal College of Engineering and Technology, Madurai, Tamil Nadu 625 009, IndiaDiabetic retinopathy (DR) is a leading cause of vision loss in diabetic patients. DR is mainly caused due to the damage of retinal blood vessels in the diabetic patients. It is essential to detect and segment the retinal blood vessels for DR detection and diagnosis, which prevents earlier vision loss in diabetic patients. The computer aided automatic detection and segmentation of blood vessels through the elimination of optic disc (OD) region in retina are proposed in this paper. The OD region is segmented using anisotropic diffusion filter and subsequentially the retinal blood vessels are detected using mathematical binary morphological operations. The proposed methodology is tested on two different publicly available datasets and achieved 93.99% sensitivity, 98.37% specificity, 98.08% accuracy in DRIVE dataset and 93.6% sensitivity, 98.96% specificity, and 95.94% accuracy in STARE dataset, respectively.http://dx.doi.org/10.1155/2015/419279 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
D. Siva Sundhara Raja S. Vasuki |
spellingShingle |
D. Siva Sundhara Raja S. Vasuki Automatic Detection of Blood Vessels in Retinal Images for Diabetic Retinopathy Diagnosis Computational and Mathematical Methods in Medicine |
author_facet |
D. Siva Sundhara Raja S. Vasuki |
author_sort |
D. Siva Sundhara Raja |
title |
Automatic Detection of Blood Vessels in Retinal Images for Diabetic Retinopathy Diagnosis |
title_short |
Automatic Detection of Blood Vessels in Retinal Images for Diabetic Retinopathy Diagnosis |
title_full |
Automatic Detection of Blood Vessels in Retinal Images for Diabetic Retinopathy Diagnosis |
title_fullStr |
Automatic Detection of Blood Vessels in Retinal Images for Diabetic Retinopathy Diagnosis |
title_full_unstemmed |
Automatic Detection of Blood Vessels in Retinal Images for Diabetic Retinopathy Diagnosis |
title_sort |
automatic detection of blood vessels in retinal images for diabetic retinopathy diagnosis |
publisher |
Hindawi Limited |
series |
Computational and Mathematical Methods in Medicine |
issn |
1748-670X 1748-6718 |
publishDate |
2015-01-01 |
description |
Diabetic retinopathy (DR) is a leading cause of vision loss in diabetic patients. DR is mainly caused due to the damage of retinal blood vessels in the diabetic patients. It is essential to detect and segment the retinal blood vessels for DR detection and diagnosis, which prevents earlier vision loss in diabetic patients. The computer aided automatic detection and segmentation of blood vessels through the elimination of optic disc (OD) region in retina are proposed in this paper. The OD region is segmented using anisotropic diffusion filter and subsequentially the retinal blood vessels are detected using mathematical binary morphological operations. The proposed methodology is tested on two different publicly available datasets and achieved 93.99% sensitivity, 98.37% specificity, 98.08% accuracy in DRIVE dataset and 93.6% sensitivity, 98.96% specificity, and 95.94% accuracy in STARE dataset, respectively. |
url |
http://dx.doi.org/10.1155/2015/419279 |
work_keys_str_mv |
AT dsivasundhararaja automaticdetectionofbloodvesselsinretinalimagesfordiabeticretinopathydiagnosis AT svasuki automaticdetectionofbloodvesselsinretinalimagesfordiabeticretinopathydiagnosis |
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1725807833621987328 |