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Skeleton extraction of cerebral vascular image based on level set model

机译:基于水平集模型的脑血管图像骨架提取

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This paper presents a new framework to calculate the continuous brain blood vessel skeleton curve of binary images and gray-scale images. The main idea of the method is: the minimum cost path between any two skeleton points is a skeleton line. Algorithm using two different intermediate functions, one is Euclidean distance field and another is deformed gradient vector flow, gained two different energy function respectively proportional to them. The topology nodes from first energy function control the shape of the object, and the second one control skeleton extraction using topology nodes as the source points. Experiment and analysis can verify the validity and robustness of this method, and not sensitive to the boundary noise.
机译:本文提出了一种计算二值图像和灰度图像的连续脑血管骨架曲线的新框架。该方法的主要思想是:任意两个骨架点之间的最小成本路径为骨架线。使用两个不同的中间函数的算法,一个是欧几里得距离场,另一个是变形的梯度矢量流,获得了两个分别与它们成比例的不同的能量函数。来自第一个能量函数的拓扑节点控制对象的形状,而第二个则使用拓扑节点作为源点控制骨骼的提取。实验和分析可以验证该方法的有效性和鲁棒性,并且对边界噪声不敏感。

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