东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2010, Vol. 31 ›› Issue (10): 1393-1396.DOI: -

• 论著 • 上一篇    下一篇

融合梯度信息的最小生成树医学图像配准

张少敏;支力佳;赵大哲;赵宏;   

  1. 东北大学信息科学与工程学院;东北大学医学影像计算教育部重点实验室;
  • 收稿日期:2013-06-20 修回日期:2013-06-20 出版日期:2010-10-15 发布日期:2013-06-20
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    辽宁省重大科技计划项目(2008402001)

Minimum spanning tree integrated with gradient information for medical image registration

Zhang, Shao-Min (1); Zhi, Li-Jia (1); Zhao, Da-Zhe (1); Zhao, Hong (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China; (2) Key Laboratory of Medical Image Computing(Ministry of Education), Northeastern University, Shenyang 110004, China
  • Received:2013-06-20 Revised:2013-06-20 Online:2010-10-15 Published:2013-06-20
  • Contact: Zhang, S.-M.
  • About author:-
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摘要： 针对传统的均匀子采样的最小生成树配准方法对采样率敏感,导致配准鲁棒性降低的问题,提出了一种融合梯度信息的最小生成树医学图像配准算法.该算法首先提取均匀子采样点集,并在此基础上构造最小生成树;然后使用最小生成树来估计Rényi熵;最后将图像间的边缘梯度信息融入到配准框架中.通过在公共数据集RREP上,与传统的基于均匀子采样的最小生成树配准算法和基于归一化互信息配准算法相比,提出的算法在达到良好配准精度的同时,具有更平滑的配准函数和较强的鲁棒性.

关键词: 医学图像配准, 最小生成树, Rényi熵, 图像梯度

Abstract: The conventional MST (minimum spanning tree) image registration based on uniform sub-sampling is so sensitive to sampling rate that the registration robustness is thus reduced. To solve the problem, MST integrated with gradient information is proposed as a medical image registration algorithm. In the algorithm, the uniform sub-sampling point set is extracted to form MST, which is used to estimate the Re´nyi entropy directly. As a result, the edge gradient information between images is integrated into the registration framework. Comparison results of the images obtained from Vanderbilt retrospective registration project (RREP) showed that the algorithm proposed can provide smoother registration function and better robustness than both the MST registration algorithm based on conventional uniform sub-sampling and the registration algorithm based on normalized mutual information (NMI).

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