同时配准-分割脑MR图像的耦合变分模型
A Variational Model for Simultaneous Registration-Segmentation to Brain MR Images
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摘要: 提出一种新颖的变分耦合模型,同时实现配准与分割.模型中使用耦合函数将非刚性配准信息与基于区域信息的曲线演化理论结合在一起,构造总能量函数,通过求解该能量函数的极值达到配准-分割的目的.该方法可以分割多模态医学图像,即使在两图间的强度信息区别较大时,也可以得到较好的分割结果.实验结果表明该方法具有较好的鲁棒性.Abstract: This paper introduces a new variational model,capable of performing registration and segmentation simultaneously.In the model a couple function is constructed to fuse the non-rigid registration information and the active contour model,based on the region information. Using this information an energy function is constructed.Through finding the extremum of the energy function the model can realize registration and segmentation simultaneously. The model can be applied to analyze the images from different modals.The results of experiments show that the model can be employed to obtain better results robustly.
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