基于小波神经网络的视网膜病变疾病自动识别

F. Yagmur, B. Karlik, A. Okatan
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引用次数: 17

摘要

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。
Automatic recognition of retinopathy diseases by using wavelet based neural network
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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