基于倾斜叠加的微动脉瘤自动检测

Jorge Oliveira, G. Minas, Carlos Alberto Silva
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引用次数: 9

摘要

眼底图像中微动脉瘤的自动检测可用于医务人员减少分析时间,允许应付筛查糖尿病视网膜病变所需的大量检查。这项工作的目的是探索Radon变换的倾斜堆叠公式,以自动检测视网膜造影上的微神经系统。Radon变换的这个公式显示出有趣的性质,即在我们的建议中探讨的Radon域上形状的不变性。该算法在Di-aretDB1上的灵敏度、特异度和准确度分别为89.46%、84.16%、84.16%,ROC下面积为0.83。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic detection of microaneurysm based on the slant stacking
The automatic detection of microaneurysms in eye fundus images can be used by medical personnel to reduce the time of analysis, permitting to cope with the high volume of exams necessary for screening the diabetic retinopathy. The goal of this work is to explore the Slant Stacking formulation of the Radon transform to automatically detect microa-neurysms on retinographies. This formulation of the Radon Transform exhibits interesting properties, namely, the invariance of the shape on the Radon domain which is explored in our proposal. The results obtained on the Di-aretDB1 with this algorithm were 89.46%, 84.16%, 84.16% for sensitivity, specificity and accuracy, respectively, while the area under the ROC was 0.83.
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