AN IMPROVED MEDICAL DECISION SUPPORT SYSTEM TO GRADING THE DIABETIC RETINOPATHY USING FUNDUS IMAGES

An improved Computer Aided Clinical Decision Support System has been developed for grading the retinal images using neural network and presented in this paper. Hard exudates, Cotton wool spots, large plaque hard exudates, Microaneurysms and Hemorrhages have been extracted. SVM classifiers have been...

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Main Authors: M. Madheswaran, S. Jerald Jeba Kumar
Format: Article
Language:English
Published: ICT Academy of Tamil Nadu 2012-11-01
Series:ICTACT Journal on Image and Video Processing
Subjects:
Online Access:http://ictactjournals.in/paper/IJIVP_VOL3_ISS2_Paper2_502_510.pdf
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author M. Madheswaran
S. Jerald Jeba Kumar
author_facet M. Madheswaran
S. Jerald Jeba Kumar
author_sort M. Madheswaran
collection DOAJ
description An improved Computer Aided Clinical Decision Support System has been developed for grading the retinal images using neural network and presented in this paper. Hard exudates, Cotton wool spots, large plaque hard exudates, Microaneurysms and Hemorrhages have been extracted. SVM classifiers have been used for classification. Further rule based classifiers have been used to grade the retinal images. The percentages of sensitivity, specificity have been found for both bright lesions and dark lesions. The accuracy of the proposed method is capable of detecting the bright and dark lesions sharply with an average accuracy of 98.19% and 97.51% respectively.
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spelling doaj.art-a80af47eef3c45109cd614d91497d4692022-12-22T03:16:34ZengICT Academy of Tamil NaduICTACT Journal on Image and Video Processing0976-90990976-91022012-11-0132502510AN IMPROVED MEDICAL DECISION SUPPORT SYSTEM TO GRADING THE DIABETIC RETINOPATHY USING FUNDUS IMAGESM. Madheswaran0S. Jerald Jeba Kumar1Center for Advanced Research, Muthayammal Engineering College, IndiaDepartment of Electronics and Communication Engineering, The Rajaas Engineering College, IndiaAn improved Computer Aided Clinical Decision Support System has been developed for grading the retinal images using neural network and presented in this paper. Hard exudates, Cotton wool spots, large plaque hard exudates, Microaneurysms and Hemorrhages have been extracted. SVM classifiers have been used for classification. Further rule based classifiers have been used to grade the retinal images. The percentages of sensitivity, specificity have been found for both bright lesions and dark lesions. The accuracy of the proposed method is capable of detecting the bright and dark lesions sharply with an average accuracy of 98.19% and 97.51% respectively.http://ictactjournals.in/paper/IJIVP_VOL3_ISS2_Paper2_502_510.pdfBright LesionDark LesionHard ExudatesCotton Wool SpotsLPHEMicroaneurysmsHemorrhagesSVMDiabetic Retinopathy(DR)Non Proliferative Diabetic Retinopathy (NPDR)
spellingShingle M. Madheswaran
S. Jerald Jeba Kumar
AN IMPROVED MEDICAL DECISION SUPPORT SYSTEM TO GRADING THE DIABETIC RETINOPATHY USING FUNDUS IMAGES
ICTACT Journal on Image and Video Processing
Bright Lesion
Dark Lesion
Hard Exudates
Cotton Wool Spots
LPHE
Microaneurysms
Hemorrhages
SVM
Diabetic Retinopathy(DR)
Non Proliferative Diabetic Retinopathy (NPDR)
title AN IMPROVED MEDICAL DECISION SUPPORT SYSTEM TO GRADING THE DIABETIC RETINOPATHY USING FUNDUS IMAGES
title_full AN IMPROVED MEDICAL DECISION SUPPORT SYSTEM TO GRADING THE DIABETIC RETINOPATHY USING FUNDUS IMAGES
title_fullStr AN IMPROVED MEDICAL DECISION SUPPORT SYSTEM TO GRADING THE DIABETIC RETINOPATHY USING FUNDUS IMAGES
title_full_unstemmed AN IMPROVED MEDICAL DECISION SUPPORT SYSTEM TO GRADING THE DIABETIC RETINOPATHY USING FUNDUS IMAGES
title_short AN IMPROVED MEDICAL DECISION SUPPORT SYSTEM TO GRADING THE DIABETIC RETINOPATHY USING FUNDUS IMAGES
title_sort improved medical decision support system to grading the diabetic retinopathy using fundus images
topic Bright Lesion
Dark Lesion
Hard Exudates
Cotton Wool Spots
LPHE
Microaneurysms
Hemorrhages
SVM
Diabetic Retinopathy(DR)
Non Proliferative Diabetic Retinopathy (NPDR)
url http://ictactjournals.in/paper/IJIVP_VOL3_ISS2_Paper2_502_510.pdf
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