Improvement of the classification accuracy in discriminating diabetic retinopathy by multifocal electroretinogram analysis  

作　　者：Xu Jin Hu Guangshu Huang Houbin 

机构地区：[1]Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China [2]Department of Ophthalmology, General Hospital of Chinese PLA, Beijing 100853, China

出　　处：《Progress in Natural Science:Materials International》2007年第8期913-918,共6页自然科学进展·国际材料（英文版）

基　　金：Supported by National Natural Science Foundation of China (Grant No.30370399)

摘　　要：The multifocal electroretinogram （mfERG） is a newly developed electrophysiological technique. In this paper, a classifi- cation 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.多焦点的网膜电图(mfERG ) 是一件最新发达的电镀物品生理的技术。在这篇论文，一个分类方法用 mfERG 数据为糖尿病的 retinopathy 的早诊断被建议。MfERG 记录在不同阶段与糖尿病从健康个人和病人的眼睛被获得。为每个 mfERG 记录， 103 本地回答被提取。所有 mfERG 本地人回答上的每个点的振幅价值被看起来象一个潜在的特征分类试验性的题目。特征子集被比较 inter-intra 距离从特征空间选择。基于选择特征子集，菲希尔的线性分类器被训练。并且记录的最后的分类决定被投票成为所有分类器的产量。使用方法分类所有试验性的题目，很低的错误率被完成。糖尿病的 retinopathy 分类方法的一些关键性质也被讨论。

关 键 词：diabetic retinopathy multifocal electroretinogram feature selection linear classifier. 

分 类 号：R587.1[医药卫生—内分泌] R774.1[医药卫生—内科学]