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Automatic Classification of Retinal Vessels Using Structural and Intensity Information

机译:使用结构和强度信息自动分类视网膜血管

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This paper presents an automatic approach for artery/vein (A/V) classification based on the analysis of a graph representing the structure of the retinal vasculature. The entire vascular tree is classified by deciding on the type of each intersection point (graph node) and assigning one of two classes to each vessel segment (graph link). The final label for each vessel segment is accomplished by a combination of structural information taken from the graph (link class) with intensity features measured in the original color image. An accuracy of 88.0% was achieved for the 40 images of the INSPIRE-AVR dataset, thus demonstrating that our method outperforms state-of-the-art approaches for A/V classification.
机译:本文基于对代表视网膜脉管系统结构的图形的分析,提出了一种自动分类动脉/静脉(A / V)的方法。通过确定每个交叉点的类型(图形节点)并为每个血管段分配两个类别之一(图形链接)来对整个血管树进行分类。每个血管段的最终标签是通过从图表(链接类)获取的结构信息与原始彩色图像中测得的强度特征的组合来完成的。 INSPIRE-AVR数据集的40张图像的准确度达到88.0%,这表明我们的方法优于最新的A / V分类方法。

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