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水平集方法在医学图像分割中的应用
引用本文:孔珊,陈相廷,刘姝月,张一凡. 水平集方法在医学图像分割中的应用[J]. 现代计算机, 2014, 0(12): 49-55
作者姓名:孔珊  陈相廷  刘姝月  张一凡
作者单位:河南大学计算机与信息工程学院,开封475001
摘    要:水平集方法已广泛应用于医学图像分割中,该方法将界面看成高一维空间中的某一函数谚(称为水平集函数)的零水平集,同时界面的演化也扩充到高一维的空间中。其核心思想是利用水平集理论求解能量泛函的最小值.即当能量达到最小值时的曲线位置就是目标轮廓所在;有效解决曲线演化过程中的拓扑变化问题。介绍水平集发展过程中几个经典模型的基本思想,并通过大量实验证明该方法在医学图像分割中的适用性及有效性。

关 键 词:水平集  医学图像分割  能量泛函  曲线演化

Application of Level-Set Method in Medical Image Segmentation
KONG Shan,CHEN Xiang-ting,LIU Shu-yue,ZHANG Yi-fan. Application of Level-Set Method in Medical Image Segmentation[J]. Modem Computer, 2014, 0(12): 49-55
Authors:KONG Shan  CHEN Xiang-ting  LIU Shu-yue  ZHANG Yi-fan
Affiliation:(College of Computer & Information Engineering, Henan University, Kaifeng 475001)
Abstract:Evolution of the level set method has been widely applied in medical image segmentation, which will screen as a higher-dimensional space in a certain function (called the level set function) of the zero level set, while also expanding the interface to a higher-dimen- sional space. The core idea is to put the level set on the mathematical theory minimum energy functional solution process, when the curve reaches a minimum energy position is where the target contour lies, effectively solving the problem of topology change in the evolu- tion of the curve which has no proper algorithm to solve previously. Describes several classical models" basic idea of the level set devel- opment and by a large number of experiments proves the applicabilitv and effectiveness of this method in medical image segmentation.
Keywords:Level Set  Medical Image Segmentation  Minimum Energy Functional  Curve Evolution
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