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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,我们提出了一种跟踪视网膜图像中的中心线曲线的数学方法。首先,从给定的图像中提取血管的无向血管拓扑图;这是在图像的二值化之后执行的。然后,我们使用骨架化算法以获得人类视网膜血管树。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,我们使用三种血管曲线的调节方法来获得平滑的曲线,特别是可能污染受试者的变形,以及识别人视网膜血管树的自然结构。在它们和血管树的几何结构之间比较了三种重建的结果。我们注意到,就平均根均方误差(RMS)值0.12像素而言,立方样条方法优于其他两种方法,以及Aximal误差(AME)0.57像素的平均绝对值。它们的优点和缺点是关于文献中提出的其他方法讨论的。

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