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Automated diagnosis of Age-related macular degeneration from color retinal fundus images

机译:从彩色视网膜眼底图像自动诊断与年龄相关的黄斑变性

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Automated image processing has the potential to assist in the early detection of Age-related macular degeneration, by detecting changes in blood vessel and patterns in the retina. Age-related macular degeneration (ARMD) is gradual loss of vision by oxidation of macula and most common cause of irreversible vision loss. The ARMD can be classified into 1. Dry macular degeneration 2. Wet macular degeneration. The purpose of this paper is to diagnose the retinal disease ARMD and to classify the two types. The extent of the disease spread in the retina can be identified by extracting the features of the retina. Detection of ARMD disease is done using Probabilistic Neural Network (PNN) method and the two types are classified and diagnosed successfully. The results showed a sensitivity of 94.00% for the classifier and specificity of 95.00%.
机译:通过检测视网膜中的血管和图案的变化,自动图像处理有可能有助于早期检测年龄相关的黄斑变性。年龄相关的黄斑变性(ARMAD)是通过氧化黄斑氧化和不可逆视力丧失的最常见原因的逐渐丧失视力。 ARMD可以分为1.干燥黄斑变性2.湿润黄斑变性。本文的目的是诊断视网膜疾病armd并分类两种类型。通过提取视网膜的特征,可以通过提取视网膜的特征来鉴定视网膜中的疾病的程度。使用概率神经网络(PNN)方法进行ARMAD疾病的检测,两种类型分类并成功诊断。结果表明,分类器的灵敏度为94.00%,特异性为95.00%。

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