[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(6):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(6):498-503.
点击复制
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(6):498-503.
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
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
3
期数:
2008年第6期
页码:
498-503
栏目:
学术论文—机器感知与模式识别
出版日期:
2008-12-25
- 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
- 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:
-
［1］WELLS Ⅲ W M, VIOLA P, ATSUMI H, et al. Multimodal volume registration by maximization of mutual information［J］. Medical Image Analysis，1996, 1(1): 35-51.
［2］MAES F, COLLIGNON A, VANDERMEULEN D,et al. Multimodality image registraion by maximization of mutual information［J］. IEEE Transactions on Medical Imaging，1997, 16(2): 187-198.
［3］STUDHOLME C, HILL D L G,HAWKES D J . An overlap invariant entropy measure of 3D medical image aligment［J］. Pattern Recognition, 1999, 32(1): 71-86.
［4］PLUIM J P W, MAINTZ J B A,VIERGEVER M A.Mutual information matching in multiresolution contexts［J］. Image and Vision Computing, 2001, 19(1/2): 45-52.
［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. Nonrigid registration using higherorder 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/.?
- 相似文献/References:
-
[1]李冰寒,高晓利,刘三阳,等.利用互信息学习贝叶斯网络结构[J].智能系统学报,2011,6(1):68.
LI-Binghan,GAO-Xiaoli,LIU-Sanyang,et al.Learning Bayesian network structures based on mutual information[J].CAAI Transactions on Intelligent Systems,2011,6():68.
[2]张昭昭,乔俊飞,杨刚.自适应前馈神经网络结构优化设计[J].智能系统学报,2011,6(4):312.
ZHANG Zhaozhao,QIAO Junfei,YANG Gang.An adaptive algorithm for designingoptimal feedforward neural network architecture[J].CAAI Transactions on Intelligent Systems,2011,6():312.
[3]宋晓丽,刘冀伟,张晓星.分布式视频编码的关键帧提取算法[J].智能系统学报,2011,6(6):539.
SONG Xiaoli,LIU Jiwei,ZHANG Xiaoxing.A key frame selection algorithm for distributed video coding[J].CAAI Transactions on Intelligent Systems,2011,6():539.
[4]周红标,乔俊飞.基于高维k-近邻互信息的特征选择方法[J].智能系统学报,2017,12(5):595.[doi:10.11992/tis.201609020]
ZHOU Hongbiao,QIAO Junfei.Feature selection method based on high dimensional k-nearest neighbors mutual information[J].CAAI Transactions on Intelligent Systems,2017,12():595.[doi:10.11992/tis.201609020]
[5]王贺彬,葛泉波,刘华平,等.面向观测融合和吸引因子的多机器人主动SLAM[J].智能系统学报,2021,16(2):371.[doi:10.11992/tis.202006019]
WANG Hebin,GE Quanbo,LIU Huaping,et al.Multi-robot active SLAM for observation fusion and attractor[J].CAAI Transactions on Intelligent Systems,2021,16():371.[doi:10.11992/tis.202006019]
[6]郑静,熊伟丽.基于互信息的多块k近邻故障监测及诊断[J].智能系统学报,2021,16(4):717.[doi:10.11992/tis.202007035]
ZHENG Jing,XIONG Weili.Multiblock k-nearest neighbor fault monitoring and diagnosis based on mutual information[J].CAAI Transactions on Intelligent Systems,2021,16():717.[doi:10.11992/tis.202007035]
[7]曲海成,王宇萍,谢梦婷,等.结合亮度感知与密集卷积的红外与可见光图像融合[J].智能系统学报,2022,17(3):643.[doi:10.11992/tis.202104004]
QU Haicheng,WANG Yuping,XIE Mengting,et al.Infrared and visible image fusion combined with brightness perception and dense convolution[J].CAAI Transactions on Intelligent Systems,2022,17():643.[doi:10.11992/tis.202104004]
[8]张智慧,杨燕,张熠玲.面向不完整多视图聚类的深度互信息最大化方法[J].智能系统学报,2023,18(1):12.[doi:10.11992/tis.202203051]
ZHANG Zhihui,YANG Yan,ZHANG Yiling.Deep mutual information maximization method for incomplete multi-view clustering[J].CAAI Transactions on Intelligent Systems,2023,18():12.[doi:10.11992/tis.202203051]
[9]余紫康,董红斌.具有混合策略的樽海鞘群特征选择算法[J].智能系统学报,2024,19(3):757.[doi:10.11992/tis.202209040]
YU Zikang,DONG Hongbin.Salp swarm feature selection algorithm with a hybrid strategy[J].CAAI Transactions on Intelligent Systems,2024,19():757.[doi:10.11992/tis.202209040]
[10]李旭,蔡彪,胡能兵.基于三元互信息的图对比学习方法研究[J].智能系统学报,2024,19(5):1257.[doi:10.11992/tis.202308004]
LI Xu,CAI Biao,HU Nengbing.Research on graph contrastive learning method based on ternary mutual information[J].CAAI Transactions on Intelligent Systems,2024,19():1257.[doi:10.11992/tis.202308004]
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