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Decision support system for diabetic retinopathy using discrete wavelet transform.
Noronha, K; Acharya, U R; Nayak, K P; Kamath, S; Bhandary, S V.
Afiliação
  • Noronha K; Department of Electronics & Communication, Manipal Institute of Technology, Manipal, India. kevinkurkal@yahoo.co.in
Proc Inst Mech Eng H ; 227(3): 251-61, 2013 Mar.
Article em En | MEDLINE | ID: mdl-23662341
Prolonged duration of the diabetes may affect the tiny blood vessels of the retina causing diabetic retinopathy. Routine eye screening of patients with diabetes helps to detect diabetic retinopathy at the early stage. It is very laborious and time-consuming for the doctors to go through many fundus images continuously. Therefore, decision support system for diabetic retinopathy detection can reduce the burden of the ophthalmologists. In this work, we have used discrete wavelet transform and support vector machine classifier for automated detection of normal and diabetic retinopathy classes. The wavelet-based decomposition was performed up to the second level, and eight energy features were extracted. Two energy features from the approximation coefficients of two levels and six energy values from the details in three orientations (horizontal, vertical and diagonal) were evaluated. These features were fed to the support vector machine classifier with various kernel functions (linear, radial basis function, polynomial of orders 2 and 3) to evaluate the highest classification accuracy. We obtained the highest average classification accuracy, sensitivity and specificity of more than 99% with support vector machine classifier (polynomial kernel of order 3) using three discrete wavelet transform features. We have also proposed an integrated index called Diabetic Retinopathy Risk Index using clinically significant wavelet energy features to identify normal and diabetic retinopathy classes using just one number. We believe that this (Diabetic Retinopathy Risk Index) can be used as an adjunct tool by the doctors during the eye screening to cross-check their diagnosis.
Assuntos
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Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Interpretação de Imagem Assistida por Computador / Retinopatia Diabética / Técnicas de Diagnóstico Oftalmológico / Análise de Ondaletas Tipo de estudo: Prognostic_studies Limite: Adult / Humans / Middle aged Idioma: En Revista: Proc Inst Mech Eng H Ano de publicação: 2013 Tipo de documento: Article
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Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Interpretação de Imagem Assistida por Computador / Retinopatia Diabética / Técnicas de Diagnóstico Oftalmológico / Análise de Ondaletas Tipo de estudo: Prognostic_studies Limite: Adult / Humans / Middle aged Idioma: En Revista: Proc Inst Mech Eng H Ano de publicação: 2013 Tipo de documento: Article