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。
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.
作者
龙邹荣
魏彪
刘平
冯鹏
柯鑫
米德伶
LONG Zourong;WEI Biao;LIU Ping;FENG Peng;KE Xin;MI Deling(College of Optoelectronic Engineering,Chongqing University,Chongqing 400044,P.R.China;Beijing Daheng Image Vision Co.Ltd,Beijing 100085,P.R.China)
出处
《重庆大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2018年第7期16-22,共7页
Journal of Chongqing University
关键词
眼底图像
渗出
阈值分割
决策树
自动检测
retinal image
exudate
threshold
decision tree
automatic detection