[1]陈伟卿,李冠华,欧宗瑛,等.基于灰度互信息和梯度相似性的医学图像配准及其加速处理[J].智能系统学报,2008,3(06):498-503.
 CHEN Wei-qing,LI Guan-hua,OU Zong-ying,et al.Medical image registration based on grey mutual information and gradient similarity with an accelerated processing method[J].CAAI Transactions on Intelligent Systems,2008,3(06):498-503.
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基于灰度互信息和梯度相似性的医学图像配准及其加速处理(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第3卷
期数:
2008年06期
页码:
498-503
栏目:
出版日期:
2008-12-25

文章信息/Info

Title:
Medical image registration based on grey mutual information and gradient similarity with an accelerated processing method
文章编号:
1673-4785(2008)06-0498-06
作者:
陈伟卿1李冠华1欧宗瑛1韩 军2
1.大连理工大学CAD & CG研究所,辽宁大连116024; 2. 大连现代高技术公司,辽宁大连116021
Author(s):
CHEN Wei-qing1LI Guan-hua1OU Zong-ying1HAN Jun2
1.CAD & CG Lab., Dalian University of Technology, Dalian 116024,China; 2.Dalian Modern HighTech Development Co.,Ltd.,Dalian 116021,China
关键词:
医学图像配准互信息加速方法梯度相似性
Keywords:
medical image registration mutual information acceleration solutions gradient similarity
分类号:
TP791.4
文献标志码:
A
摘要:
研究基于归一化互信息的医学图像刚性配准算法,提出改进配准速度和改善配准精度的相应措施.配准处理包含3项主要计算处理,即空间变换、互信息计算以及优化搜索.针对不同计算处理分别研究了相应加速策略,提高其计算速度,实现三维体数据的快速配准.并且,针对传统基于互信息测度配准方法未利用图像灰度空间分布信息,提出将灰度变化梯度相似性与互信息相结合的配准方法,从而进一步提高了配准算法的精度和鲁棒性.实验结果表明了算法的有效性.
Abstract:
This paper presents new methods that have been developed for rigid registration of medical images. These methods are based on normalized mutual information and improve registration speed and precision. The whole registration process includes three main steps: space transformation, mutual information calculation, and optimal search. Some acceleration strategies for fast registration of 3D volume data were investigated. Conventional registration approaches, based on mutual information, neglect the spatial distribution information of images. In view of this drawback, a new method was developed, combining data based on gradient similarity and mutual information. This improves the precision and robustness of the registration algorithm. Experimental results proved the validity of the proposed methods.

参考文献/References:

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[5]ZHU Y M,COCHOFFS M. Influence of implementation parameters on registration of MR SPECT brain images by maximization of mutual information[J]. Journal of Nuclear Medicine, 2002, 43(2): 160-166.
[6]秦斌杰,庄天戈. 三维多模态医学图像配准系统的设计[J]. 上海交通大学学报, 2003, 37(2): 228-231.
QIN Binjie, ZHUANG Tiange. Multi resolution registration system design for 3D multi-modal medical images[J]. Journal of Shanghai Jiaotong University, 2003, 37(2): 228-231.
[7]WACHOWIAK M P,PETERS T M. High performance medical image registration using new optimization techniques[J]. IEEE Transactions on Information Technology in Biomedicine, 2006, 10(2): 344-352.
[8]WACHOWIAK M P,SMOLIKOVA R, PETERS T M. Multiresolution biomedical image registration using generalized information measures//[C].Proc MICCAI 2003.New York,USA, 2003:846-853.
[9]RUECKERT D, CLARKSON M J,HILL D L J,et al. Nonrigid registration using higherorder mutual information[C]//Proceedings of SPIE Medical Imaging. San Diego, USA,2000:438- 447.
[10]WANG X X,TIAN J. Image registration based on maximization of gradient code mutual information[J]. Image Anal Stereol, 2005, 24:1-7.
[11]COCOSCO C A,KOLLOKIAN V,KWAN R K S.Brainweb:Online interface to a 3D MRI simulated brain database[EB/OL]. (2006-06-12)[2008-06-18].http://www.bic.mni.mcgill.ca/brainweb/. 

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备注/Memo

备注/Memo:
收稿日期:2008-07-02.
基金项目:国家863计划资助项目(863-306-ZD13- 03-6).
作者简介:
陈伟卿,女,1976年生,博士研究生,主要研究方向为图像处理分析与理解.
李冠华,男,1979年生,博士研究生,主要研究方向为图像处理与三维可视化.
欧宗瑛,男,1936年生,教授,博士生导师,主要研究方向为计算机辅助设计、计算机图像学与图像处理.获省级科技一等奖1项,三等奖2项及参编科技图书二等奖、教材二等奖各1项.发表的学术论文被SCI检索12篇,被EI检索100余篇.
更新日期/Last Update: 2009-04-03