• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2012, Vol. 34 ›› Issue (12): 110-114.

• 论文 • 上一篇    下一篇

基于形状和灰度信息的断层图像二次配准算法

刘君1,2,武和雷3   

  1. (1.南昌大学机电工程学院,江西 南昌 330031;2.南昌航空大学信息工程学院,江西 南昌 3300633.南昌大学信息工程学院,江西 南昌 330031)
  • 收稿日期:2011-11-24 修回日期:2012-02-27 出版日期:2012-12-25 发布日期:2012-12-25
  • 基金资助:

    国家自然科学基金资助项目61163047(61163047);江西省自然科学基金资助项目(2010GQS0166);江西省教育厅基金资助项目(GJJ10191)

A Tomography Image ReRegistration Algorithm Based on Frame and Gray Information

LIU Jun1,2,WU Helei3   

  1. (1.School of Mechatronics,Nanchang University,Nanchang 330031;
    2.School of Information Engineering,Nanchang Hang Kong University,Nanchang 330063;3.School of Information Engineering,Nanchang University,Nanchang 330031,China)
  • Received:2011-11-24 Revised:2012-02-27 Online:2012-12-25 Published:2012-12-25

摘要:

将一种新的基于形状信息和灰度信息的二次配准方法引入CTMRI配准过程,首先通过力学分解的原理描述了两幅待配准图像的轮廓,并利用该轮廓对两幅图像进行粗配准,通过该方法将两幅图像的配准误差限定到一个较小范围内;继而利用最大互信息的方法继续对经过粗配准的两幅图像进行二次配准,最终得到精度更高的配准效果。仿真结果表明,由于该算法结合了轮廓比对方法的高效性和最大互信息方法的精确性,因此与其它配准算法相比在保证了配准精度的同时大大缩短了配准时间。最后该算法被成功地应用到了准备进行开颅手术的病人的CTMRI图像配准上。

关键词: 图像配准, 互信息, 神经网络, 粒子群优化

Abstract:

In this paper, a new reregistration method that based on shape information and gray information is introduced into the procedure of the CTMRI registration. Firstly, the frames of the two images to be registered are explained by the principle of mechanics decomposition, then we coarsely register the two images by their frames and as a result the error of the registration is constrained in a small region. Secondly, we reregister the two images that have been coarsely registered by means of the maximum mutual information (MMI), and finally an accurate registration result is obtained. The simulation result shows that, as this method combines the efficiency of the framebased registration method and the accuracy of the MMIbased registration method, this method is less time consuming and on the other side the registration accuracy is also guaranteed in comparison with other methods. Finally we successfully apply the present method to register the CT images and MRI images in a patient undergoing neurosurgery.

Key words: image registration;mutual information;neural network;particle swarm optimization