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Improved Live-Wire algorithm for kidney image segmentation

机译:改进的肾图像分割实时线算法

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摘要

Live-Wire segmentation algorithm is an interactive tool for efficient, accurate and reproducible boundary extraction which requires minimal user input. But the traditional Live-Wire algorithm is sensitive to noise and inefficient to distinguish between strong and weak edges in the image. To overcome the two drawbacks, this paper proposes an improved Live-Wire algorithm, its cost function is redefined: (1) change the Laplace operator into Canny and Sobel operators to construct the multiple cost terms, differences between Canny and Sobel operators allow them to contribute to the total cost calculation without redundant information; (2) redefine the gradient magnitude function of the cost function as nonlinear weighting edge gradient, the nonlinear weighting procedure can solve the undistinguished edge problem very well. Experiments are conducted on simulation and real image of the kidney. The experimental results prove that the proposed algorithm is really of good performance in the two drawbacks.
机译:实时线路分割算法是一种用于高效,准确和可重复的边界提取的交互式工具,其需要最小的用户输入。但传统的Life-Wire算法对噪声和效率敏感,以区分图像中的强且弱边缘。为了克服这两个缺点,本文提出了一种改进的Life-Wire算法,其成本函数重新定义:(1)将拉普拉斯算子更改为Canny和Sobel运算符以构建多重成本术语,Canny和Sobel运营商之间的差异允许它们允许它们没有冗余信息的总成本计算贡献; (2)将成本函数的梯度幅度函数重新定义为非线性加权边缘梯度,非线性加权程序可以很好地解决不区分的边缘问题。对肾脏的仿真和真实形象进行了实验。实验结果证明,该算法在两个缺点中的表现非常好。

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