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Automatic Estimation of the Arteriolar-to-Venular Ratio in Retinal Images Using a Graph-Based Approach for Artery/Vein Classification

机译:基于图的动脉/静脉分类的基于图的方法自动估计视网膜图像中的动脉瘤 - 瓣膜比

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The Arteriolar-to-Venular Ratio (AVR) is a well known index for the diagnosis of diseases such as diabetes, hypertension or cardiovascular pathologies. This paper presents a fully automatic AVR estimation method which uses a graph-based artery/vein classification approach to classify the retinal vessels by a combination of structural information taken from the vasculature graph with intensity features from the original color image. This method was evaluated on the images of the INSPIRE-AVR dataset. The mean error and the correlation coefficient of obtained results with respect to the reference AVR values were identical to the ones obtained by the second observer using a semi-automated system, which demonstrate the potential of the herein proposed solution for clinical application.
机译:动脉杆状血清比(AVR)是识别糖尿病,高血压或心血管病理等疾病的众所周知的指标。本文介绍了一种全自动的AVR估计方法,它使用基于图的动脉/静脉分类方法来通过从原始彩色图像的强度特征的结构信息的结构信息的组合来分类视网膜血管。在Inspire-AVR数据集的图像上评估该方法。所获得的关于参考AVR值的平均误差和相关系数与使用半自动系统获得的第二观察者获得的结果相同,这证明了本文提出的临床应用的潜力。

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