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首页 > 过刊浏览>2018年第41卷第7期 >16-22. DOI:10.11835/j.issn.1000-582X.2018.07.003
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基于决策树的眼底图像渗出自动检测方法
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TU411


An automatic detection method for retinal exudation based on decision tree
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    摘要:

    自动视网膜图像渗出检测有助于糖尿病性视网膜病变的早期诊断，提出了彩色眼底图像视网膜渗出检测方法。该方法根据决策树理论，采用Messidor数据库，对视网膜图像进行分类，区分得到含渗出的病变图像和不含渗出的正常眼底图像。实验结果表明，针对不同光照下采集的眼底图像采用光照非均匀性的归一化处理，即使在光照变化的环境中，文中的方法仍然比眼科专家的人工判定表现出色，能很好地分割出渗出区域。

    Abstract:

    Automatic detection of retinal image exudation is helpful for early diagnosis of diabetic retinopathy. According to the decision tree theory, we propose a retinal intrusion detection method based on color fundus images and test it with Messidor database. It can help us to distinguish the diseased images and normal fundus images. The experimental results show that this method is better than the eye specialist's manual judgment in that it can detect exudation area more accurately in a changing enviroment of light by the integration of images.

    参考文献
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龙邹荣,魏彪,刘平,冯鹏,柯鑫,米德伶.基于决策树的眼底图像渗出自动检测方法[J].重庆大学学报,2018,41(7):16-22.

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  • 收稿日期:2017-12-19
  • 在线发布日期: 2018-07-19
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