Automatic recognition of retinopathy diseases by using wavelet based neural network

2008 First International Conference on the Applications of Digital Information and Web Technologies (ICADIWT) Pub Date : 2008-10-31 DOI:10.1109/ICADIWT.2008.4664391

F. Yagmur, B. Karlik, A. Okatan

引用次数: 17

Abstract

In this study, recognition of five types of retina disorders and normal retina has been studied. The names of these five different Retinopathies are: Diabetic Retinopathy, Hypertensive retinopathy, Macular Degeneration, Vein Branch Oclusion, Vitreus hemorrhage, and normal retina. A wavelet based neural network architecture has been used to diagnose retinopathy automatically. In the process, the retina images were pre-processed and resized. Later, feature extraction has been done before applying into classifier. The performance of proposed method has been found very high. The recognition rates were found %50, %70, %83, %90, %93 and %95 for testing five retinopathy cases respectively.

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基于小波神经网络的视网膜病变疾病自动识别

在本研究中，对五种视网膜疾病和正常视网膜的识别进行了研究。这五种视网膜病变的名称分别是:糖尿病视网膜病变、高血压视网膜病变、黄斑变性、静脉分支闭塞、玻璃体出血和正常视网膜。采用基于小波的神经网络结构对视网膜病变进行了自动诊断。在这个过程中，视网膜图像被预处理和调整大小。然后，在应用于分类器之前进行特征提取。实验结果表明，该方法具有很高的性能。5例视网膜病变的识别率分别为% 50%、% 70%、% 83%、% 90%、% 93%和% 95%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2008 First International Conference on the Applications of Digital Information and Web Technologies (ICADIWT)

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