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Artificial neural network and system for identifying lesion in retinal fundus image

机译:识别视网膜眼镜图像中病变的人工神经网络和系统

摘要

The present disclosure provides an artificial neural network system for identifying a lesion in a retinal fundus image that comprises a pre-processing module configured to separately pre-process a target retinal fundus image and a reference retinal fundus image taken from a same person; a first neural network (12) configured to generate a first advanced feature set from the target retinal fundus image; a second neural network (22) configured to generate a second advanced feature set from the reference retinal fundus image; a feature combination module (13) configured to combine the first advanced feature set and the second advanced feature set to form a feature combination set; and a third neural network (14) configured to generate, according to the feature combination set, a diagnosis result. By using a target retinal fundus image and a reference retinal fundus image as independent input information, the artificial neural network may simulate a doctor, determining lesions on the target retinal fundus image using other retinal fundus images from the same person as a reference, thereby enhancing the diagnosis accuracy.
机译:本公开提供了一种用于识别视网膜眼底图像中的病变的人工神经网络系统,其包括预处理模块,该预处理模块被配置为单独预处理目标视网膜眼镜图像和来自同一个人的参考视网膜眼底图像;第一神经网络(12),用于生成从目标视网膜眼底图像设置的第一高级特征;第二神经网络(22),其被配置为生成从参考视网柱眼底图像设定的第二高级特征;特征组合模块(13)被配置为组合第一高级功能集和第二高级功能集以形成特征组合集;和第三神经网络(14)被配置为产生根据特征组合集生成诊断结果。通过使用目标视网膜眼底图像和参考视网膜眼底图像作为独立输入信息,人工神经网络可以模拟医生,使用与同一个人的其他视网膜眼底图像作为参考的其他视网膜眼底图像确定病变,从而增强诊断精度。

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