Improvement of the classification accuracy in discriminating diabetic retinopathy by multifocal electroretinogram analysis
Improvement of the classification accuracy in discriminating diabetic retinopathy by multifocal electroretinogram analysis
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DOI：
10.1080/10002007088537491
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发表时间：
2007-08
期刊：
影响因子：
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通讯作者：
Xu Jin;Hu Guang-shu;Huang Hou-bin
中科院分区：
文献类型：
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作者：
Xu Jin;Hu Guang-shu;Huang Hou-bin
摘要多焦视网膜电信号(MfERG)是一种新发展起来的电生理技术。提出了一种利用mfERG数据对糖尿病视网膜病变进行早期诊断的分类方法。MfERG记录来自不同阶段的健康人和糖尿病患者的眼部。对于每个mfERG记录，提取了103个本地响应。所有mfERG局部反应的每个点的幅值被视为一个潜在的特征来对实验对象进行分类。通过比较帧内距离从特征空间中选择特征子集。基于选取的特征子集，训练Fisher的线性分类器。记录的最终分类决定是通过投票所有分类器的输出来做出的。应用该方法对所有实验对象进行分类，获得了很低的错误率。文中还讨论了糖尿病视网膜病变分类方法的一些重要性质。*国家自然科学基金S资助...
Abstract The multifocal electroretinogram (mfERG) is a newly developed electrophysiological technique. In this paper, a classification method is proposed for early diagnosis of the diabetic retinopathy using mfERG data. MfERG records were obtained from eyes of healthy individuals and patients with diabetes at different stages. For each mfERG record, 103 local responses were extracted. Amplitude value of each point on all the mfERG local responses was looked as one potential feature to classify the experimental subjects. Feature subsets were selected from the feature space by comparing the inter-intra distance. Based on the selected feature subset, Fisher's linear classifiers were trained. And the final classification decision of the record was made by voting all the classifiers' outputs. Applying the method to classify all experimental subjects, very low error rates were achieved. Some crucial properties of the diabetic retinopathy classification method are also discussed. *Supported by National Natural S...