Application of the level-set model with constraints in image segmentation
Application of the level-set model with constraints in image segmentation
复制标题
带约束的水平集模型在图像分割中的应用
DOI：
10.4208/nmtma.2015.m1418
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
Daniel vSevvcovivc
中科院分区：
文献类型：
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作者：
V. Klement;Tom'avs Oberhuber;Daniel vSevvcovivc
提出并分析了一种用于半自动图像分割的约束水平集方法。我们的水平集模型带有水平集函数的约束，使我们能够指定图像的哪些部分分别位于分割对象的内部和外部。这样的先验信息可以用为水平集函数规定的上限和下限约束来表示。约束与流行的基于图割的图像分割方法的初始种子具有相同的概念意义。采用互补有限体积法和投影逐次超松弛法相结合的数值逼近格式来求解约束线性互补问题。在几幅人工图像和心脏核磁共振数据上验证了约束水平集方法的优越性。
We propose and analyze a constrained level-set method for semi-automatic image segmentation. Our level-set model with constraints on the level-set function enables us to specify which parts of the image lie inside respectively outside the segmented objects. Such a-priori information can be expressed in terms of upper and lower constraints prescribed for the level-set function. Constraints have the same conceptual meaning as initial seeds of the popular graph-cuts based methods for image segmentation. A numerical approximation scheme is based on the complementary-finite volumes method combined with the Projected successive over-relaxation method adopted for solving constrained linear complementarity problems. The advantage of the constrained level-set method is demonstrated on several artificial images as well as on cardiac MRI data.
DOI：
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发表时间：
2007-12
期刊：
arXiv: Numerical Analysis
影响因子：
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作者：
M. Beneš;M. Kimura;P. Paus;D. Ševčovič;T. Tsujikawa;S. Yazaki
通讯作者：
M. Beneš;M. Kimura;P. Paus;D. Ševčovič;T. Tsujikawa;S. Yazaki