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Hierarchical elastic registration of human brain images based on wavelet decomposition

机译:基于小波分解的人脑图像分层弹性配准

摘要

Wavelets have been studied and applied in the multimedia and video processing community, including some areas in medical imaging, however, wavelet-based medical image registration has not been explored properly. In this paper, we propose an hierarchical registration method based on wavelet decomposition. Firstly, based on the wavelets, the images are decomposed into subbands which compose the registration pyramid; then, in each hierarchy, the affine registration based on mutual information is performed and the results of the current registration are used as the initial guess for the next hierarchy; finally, to further improve the registration performance, the local elastic registration is carried out. The proposed algorithm has been validated by experiments on clinical tomographic images and our experimental results demonstrate the the proposed method is of efficiency and good accuracy.
机译:小波已经在多媒体和视频处理社区中得到了研究和应用,包括医学成像的某些领域,但是,基于小波的医学图像配准尚未得到适当的探索。本文提出了一种基于小波分解的分层配准方法。首先,基于小波将图像分解为组成配准金字塔的子带。然后,在每个层次中,执行基于互信息的仿射注册,并将当前注册的结果用作下一个层次的初始猜测;最后,为了进一步提高配准性能,进行局部弹性配准。通过对临床断层图像的实验验证了该算法的有效性,实验结果证明了该方法的有效性和准确性。

著录项

  • 作者

    Wang X; Feng DD;

  • 作者单位
  • 年度 2004
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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