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ARTIFICIAL NEURAL NETWORK AND SYSTEM FOR IDENTIFYING LESION IN RETINAL FUNDUS IMAGE

机译:人工神经网络和系统识别视网膜眼底图像的病变

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,被配置为分别对从同一人获取的目标视网膜眼底图像和参考视网膜眼底图像进行预处理。第一神经网络( 12 ),用于从目标视网膜眼底图像生成第一高级特征集;第二神经网络( 22 ),用于从参考视网膜眼底图像生成第二高级特征集;特征组合模块( 13 ),用于组合第一高级特征集和第二高级特征集以形成特征组合集;第三神经网络( 14 ),用于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,使用来自同一人的其他视网膜眼底图像作为参考,确定目标视网膜眼底图像上的病变,从而增强诊断准确性。

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