A fast algorithm for automatic segmentation and extraction of a single object by active surfaces

A fast algorithm for automatic segmentation and extraction of a single object by active surfaces
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一种通过活动表面自动分割和提取单个对象的快速算法

DOI:
10.1080/00207160.2014.931943
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发表时间:
2015-06
影响因子:
1.8
通讯作者:
Gould, Derek A.
Gould, Derek A.
中科院分区:
数学4区
文献类型:
--
作者:
Zhang, Jianping;Chen, Ke;Gould, Derek A.

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分割是各种应用中的一个重要问题。存在许多有效的模型,旨在定位图像中的所有特征及其边界。然而,这种全局模型不适合自动检测图像的许多对象中的单个对象,因为附近的对象通常也会被选择。最近的几项工作可以提供选择性分割能力,但不幸的是,当推广到三维时,它们还不够有效或高效。本文提出了一种本质上适合高效实施的选择性分割模型。通过针对零水平集函数的内部域添加快速非线性多重网格方法的求解器,过度方法产生了用于 3D 选择性分割的有效且高效的算法。数值实验表明,我们的模型可以在大类 3D 图像的分割质量和可靠性方面产生有效的结果。
Segmentation is an important problem in various applications. There exist many effective models designed to locate all features and their boundaries in an image. However such global models are not suitable for automatically detecting a single object among many objects of an image, because nearby objects are often selected as well. Several recent works can provide selective segmentation capability but unfortunately when generalized to three dimensions, they are not yet effective or efficient. This paper presents a selective segmentation model which is inherently suited for efficient implementation. With the added solver by a fast nonlinear multigrid method for the inside domain of a zero level set function, the over methodology leads to an effective and efficient algorithm for 3D selective segmentation. Numerical experiments show that our model can produce efficient results in terms of segmentation quality and reliability for a large class of 3D images.
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