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Computer method for tracking the centerline curve of the human retinal blood vessel

机译:跟踪人视网膜血管中心线曲线的计算机方法

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In this paper, we propose a mathematical approach for tracking the centerline curve in retinal images. First, the undirected topology graph of the blood vessel is extracted from the given image; this is performed after the binarization of the image. Then, we use a skeletonization algorithm in order to obtain the human retinal vascular tree. Next, we determinate the pixels classification (endpoints, bifurcation points, and interior points) and branches curve. Finally, we use three methods of reconciliation of the blood vessels curve to get a smooth curve, particularly insensitive to deformations that may taint the subject, as well as the recognition of the natural structures of the human retinal vascular tree. The results obtained for the three types of reconstruction are compared between them and with the geometrical structure of the vascular tree. We note that the cubic spline method is better than the other two methods in terms of average Root-Mean-Square Error (RMS) value 0.12 pixels and the average Absolute value of the Aaximal Error (AME) 0.57 pixel. Their advantages and disadvantages are discussed in relation to other methods proposed in the literature.
机译:在本文中,我们提出了一种用于跟踪视网膜图像中线曲线的数学方法。首先,从给定图像中提取血管的无向拓扑图;这是在图像二值化之后执行的。然后,我们使用骨架化算法以获得人的视网膜血管树。接下来,我们确定像素分类(端点,分叉点和内部点)和分支曲线。最后,我们使用三种调节血管曲线的方法来获得平滑的曲线,特别是对可能弄脏受试者的变形不敏感,以及对人类视网膜血管树的自然结构的识别不敏感。将三种重建类型的结果与血管树的几何结构进行比较。我们注意到,三次样条曲线方法在平均均方根误差(RMS)值0.12像素和平均绝对误差(AME)0.57像素的平均值方面优于其他两种方法。结合文献中提出的其他方法讨论了它们的优缺点。

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