Image processing based automatic diagnosis of glaucoma using wavelet features of segmented optic disc from fundus image
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- 作者：Anushikha Singha ; anushikha4june@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Malay Kishore Duttaa ; malaykishoredutta@gmail.com" class="auth_mail" title="E-mail the corresponding author ; M. ParthaSarathia ; infiniti47@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Vaclav Uherb ; vaclav.uher@phd.feec.vutbr.cz" class="auth_mail" title="E-mail the corresponding author ; Radim Burgetb ; burgetrm@feec.vutbr.cz" class="auth_mail" title="E-mail the corresponding author
- 关键词：Glaucoma ; Fundus image ; Blood vessels ; Wavelet transform ; Feature extraction ; Classification
- 刊名：Computer Methods and Programs in Biomedicine
- 出版年：2016
- 出版时间：February 2016
- 年：2016
- 卷：124
- 期：Complete
- 页码：108-120
- 全文大小：1399 K
文摘
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In this work glaucoma identification is done using wavelet features of optic disk.
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Wavelet features are extracted from segmented and blood vessels removed optic disk.
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Several machine learning algorithms are used for prominent feature selection.
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Genetic algorithm is used to reduce the dimensionality of feature vector.
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Accuracy of glaucoma identification achieved in this work is 94.7%.