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Multiphase level set with multi dynamic shape models on kidney segmentation of CT image

机译:多相水平集与多动态形状模型在CT图像肾脏分割中的应用

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In this paper, a multiphase level set method with multi dynamic shape models is proposed to segment the kidneys on the abdominal computed tomography (CT) images. Comparing with the original Chan-Vese model three changes are made to improve the segmentation result. The first is using shape model to help the segmentation. The second is using dynamic shape model to deal with the variation of the kidneys. The third is using multi level set to simultaneously segment multi objects. We also develop an algorithm to automatically get the initial level set curves and initial shape models which are essential to apply the proposed method. In the experiments, the proposed method is compared with the Chan-Vese model and the single level set method with shape prior to prove that the proposed method can work better on the kidneys segmentation.
机译:本文提出了一种具有多动态形状模型的多阶段水平集方法,以在腹部计算机断层扫描(CT)图像上分割肾脏。与原始的Chan-Vese模型相比,进行了三个更改以改善分割结果。首先是使用形状模型来帮助分割。第二个是使用动态形状模型来处理肾脏的变化。第三是使用多级集同时分割多个对象。我们还开发了一种算法,可以自动获取初始水平设置曲线和初始形状模型,这对于应用该方法至关重要。在实验中,将所提出的方法与Chan-Vese模型和具有形状的单水平集方法进行比较,以证明所提出的方法可以更好地进行肾脏分割。

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