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Locally Adaptive Operators for Red Lesions Detection in Eye Fundus Images

机译:局部自适应运算符在眼底图像中的红色病变检测

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One of the major features required by automated software tools of screening for diabetic retinopathy is the detection of red lesions. This paper presents a new automatic method in order to locate red lesions in color eye fundus images. The method relies on mathematical morphology operators and has a coarse and a fine detection stages, respectively. The former detection stage detects structures oflow-intensity values in the retina, such as microaneurysms, hemorrhages, blood vessels and the fovea center. Additionally, the latter stage proposes to improve the detection of red lesions identified in the previous stage. For experiments, we use the well-known publicly available DIARETDB1 database. The results indicate that our method detected red lesions with 75.81% and 93.48% of mean sensitivity and mean specificity, respectively.
机译:自动化软件筛选糖尿病视网膜病变的自动化软件工具需要的一个主要特征是检测红色病变。本文呈现了一种新的自动方法,以定位在彩色眼底图像中的红色病变。该方法依赖于数学形态学运算符,并分别具有粗略和精细检测阶段。以前的检测阶段检测视网膜中的强度值的结构,例如微内肌瘤,出血,血管和FOVEA中心。另外,后期阶段提出改善前一阶段中鉴定的红色病变的检测。对于实验,我们使用众所周知的公开可用的DiaRetdB1数据库。结果表明,我们的方法分别检测到具有75.81%和93.48%的平均敏感性和平均特异性的红色病变。

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