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基于形状特征点最大互信息的医学图像配准

Medical Image Registration Based on Mutual Information of Feature Points

  • 摘要: 定义了基于形状特征点的互信息计算公式,提出区域增长结合动态聚类算法的形状特征点提取方法.在使形状特征点互信息最大化完成医学图像配准的过程中,引入人机交互,缩短了优化过程,避免了局部极值.提出的配准策略具备临床实用性,尤其适于缺少灰度信息的医学图像配准.

     

    Abstract: Mutual information representing the anatomic features of medical image is computed with feature points.The feature points are extracted from images using region growing and dynamic clustering.During maximization of the mutual information to accomplish image registration,man-machine interaction is used to facilitate this procedure and a ransack method is also adopted to avoid local extrema.Preliminary results on twodimensional robust alignment of MRI-MRI images and MRI-CTimages are presented.The registration strategy presented here might be suitable to clinical applications,especially for images without gray level information.

     

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