Please wait a minute...
J4  2012, Vol. 46 Issue (9): 1722-1728    DOI: 10.3785/j.issn.1008-973X.2012.09.027
生物医学工程     
基于吸引区域的多模态脑磁共振图像仿射配准
孙创日1,2,甄帅1,夏顺仁1
1. 浙江大学 生物医学工程教育部重点实验室,浙江 杭州310027;2. 金策工业综合大学 电子系, 朝鲜 平壤104919
Attractor range based affine registration of multi-modal
brain magnetic resonance images
SON Chang-il1, 2 , ZHEN Shuai1, XIA Shun-ren1
1.Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou 310027, China;
2.Department of Electronics, Kim Chaek University of Technology, Pyongyang 104919, DPR of Korea
 全文: PDF  HTML
摘要:

针对单个对象的多模态脑磁共振图像之间的几何形变较小的情形,为达到全局优化的目的,提出一种基于吸引区域的多模态脑磁共振图像仿射配准方法.把配准优化搜索过程分成两个步骤:寻找包含全局最小值的吸引区域和在吸引区域中进行最小值搜索.该配准优化使用吸引区域里目标函数的近似对称性予以实现.对于正常人群和脑胶质瘤患者群,进行了磁共振 T1加权和扩散加权图像之间多模态配准实验,并使用两种相似测度对3种不同的配准方法进行评价,实验结果表明:该方法与传统的局部优化方法相比,配准后的相似性测度均有显著性改善.

Abstract:

In view of the fact  that the geometrical deformation between multi-modal brain magnetic resonance images(MRI) of the single subject is small,  a  attractor range based method for affine registration between multimodal brain MRI  was proposed to achieve the global optimization.  The process of registration optimization search was divided into two steps: the search for “attractor range” which contained the global minimum, and the search for global minimum within the attractor range. The registration optimization was realized by using the approximate symmetry of the objective function in the attractor range. The multi-modal registration experiments between MRI T1-weighted and diffusion weighted brain images were performed for a healthy control group and a patient group with glioma, and two similarity measures were used to evaluate three different registration algorithms. Compared with the traditional schemes using local optimization, the registration quality using the proposed algorithm was significantly improved.

出版日期: 2012-09-01
:  TP 391.41  
基金资助:

国家自然科学基金资助项目(81101903,60772092).

通讯作者: 夏顺仁,男,教授,博导.     E-mail: srxia@zju.edu.cn
作者简介: 孙创日(1970-),男,博士生,主要从事医学图像处理研究.E-mail: sunchuangri@zju.edu.cn
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  

引用本文:

孙创日,甄帅,夏顺仁. 基于吸引区域的多模态脑磁共振图像仿射配准[J]. J4, 2012, 46(9): 1722-1728.

SON Chang-il , ZHEN Shuai, XIA Shun-ren. Attractor range based affine registration of multi-modal
brain magnetic resonance images. J4, 2012, 46(9): 1722-1728.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2012.09.027        http://www.zjujournals.com/eng/CN/Y2012/V46/I9/1722

[1] GERING T D, NABAVI A, KIKINIS R, et al. An integrated visualization system for surgical planning and guidance using image fusion and an open MR [J]. Journal of Magnetic Resonance Imaging, 2001, 13(6): 967-975.
[2]NISHIOKA T, SHIGA T, SHIRATO H, et al. Image fusion between (18) FDGPET and MRI/CT for radiotherapy planning of oropharyngeal and nasopharyngeal carcinomas [J]. International Journal Radiation Oncology, Biology, Physics, 2002, 53(4): 1051-1057.
[3] LANCASTER J L, TORDESILLASGUTIERREZ D, MARTINEZ M, et al. Bias between MNI and talairach coordinates analyzed using the ICBM152 brain template [J]. Human Brain Mapping, 2007, 28(11): 1194-1205.
[4] JENKINSON M, BANNISTER P, BRADY M, et al, Improved optimization for the robust and accurate linear registration and motion correction of brain images [J]. NeuroImage, 2002, 17(2): 825-841.
[5] MOHAMMADI S, MLLER E H, KUGEL H, et al. Correcting eddy current and motion effects by affine wholebrain registrations: Evaluation of threedimensional distortions and comparison with slicewise correction [J]. Magnetic Resonance in Medicine, 2010, 64(4): 1047-1056.
[6] 陈显毅. 图像配准技术及其Matlab编程实现[M]. 北京: 电子工业出版社,2009: 1-232.
[7] 罗述谦, 周果宏. 医学图像处理与分析[M]. 北京: 科学出版社,2003: 140-202.
[8] STEFAN K, JOSIEN P P, MARIUS S, et al. elastix: A toolbox for intensitybased medical image registration [J]. IEEE Transactions on Medical Imaging, 2010, 29 (1): 196-205.
[9] WILLIAM H P, TEUKOLSKY A S, WILLIAM T V, et al. Numerical recipes in C[M]. Cambridge: Cambridge University Press, 1997: 394-455.
[10] MAES F, VANDERMEULEN D., SUETENS P. Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information [J]. Medical Image Analysis, 1999, 3 (4): 373-386.
[11] MAES F, COLLIGNON A, VARNDERMEULEN D, et al. Multimodality image registration by maximization of mutual information [J]. IEEE Transactions on Medical Imaging, 1997, 16(5): 187-198.
[12] JENKINSON M, SMITH S. A global optimisation method for robust affine registration of brain images [J]. Medical Image Analysis, 2001, 5(2): 143-156.
[13] SMITH S M, JENKINSON M, WOOLRICH M W, et al. Advances in functional and structural MR image analysis and implementation as FSL [J]. NeuroImage, 2004, 23 (1): 208-219.
[14] FRISTON K J, ASHBURNER J, POLINE J B, et al. Spatial registration and normalization of images [J]. Human Brain Mapping, 1995, 3(3):165-189.
[15] SMITH S M. Fast robust automated brain extraction [J]. Human Brain Mapping, 2002, 17(3):143-155.
[16] KLEIN A, ANDERSSON J, ARDEKANI B A, et al.Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration [J]. NeuroImage, 2009, 46(3):786-802.

[1] 杨玉婷, 史玉回, 夏顺仁. 基于讨论机制的头脑风暴优化算法[J]. J4, 2013, 47(10): 1705-1711.
[2] 朱晓恩, 郝欣, 夏顺仁. 基于Levy flight的特征选择算法[J]. J4, 2013, 47(4): 638-643.
[3] 谢迪, 童若锋, 唐敏, 冯阳. 具有高区分度的视频火焰检测方法[J]. J4, 2012, 46(4): 698-704.
[4] 李启雷, 金文光, 耿卫东. 基于无线惯性传感器的人体动作捕获方法[J]. J4, 2012, 46(2): 280-285.
[5] 戴渊明, 韦巍, 林亦宁. 基于颜色纹理特征的均值漂移目标跟踪算法[J]. J4, 2012, 46(2): 212-217.
[6] 刘晨彬,潘颖,张海石,黄峰平,夏顺仁. 基于磁共振图像的脑瘤MGMT表达状况检测算法[J]. J4, 2012, 46(1): 170-176.
[7] 钱诚, 张三元. 适用于目标跟踪的加权增量子空间学习算法[J]. J4, 2011, 45(12): 2240-2246.
[8] 吕谷来, 李建平, 李锵, 俞利兴, 朱松明, 楼建忠, 袁祎琳. 基于机器视觉的砧木定位识别方法[J]. J4, 2011, 45(10): 1766-1770.
[9] 曹颖, 郝欣, 朱晓恩, 夏顺仁. 基于自动随机游走的乳腺肿块分割算法[J]. J4, 2011, 45(10): 1753-1760.
[10] 赖小波,朱世强. 基于互相关信息的非参数变换立体匹配算法[J]. J4, 2011, 45(9): 1636-1642.
[11] 王金德, 寿黎但, 李晓燕, 陈刚. 基于多重分割捆绑特征的目标图像检索[J]. J4, 2011, 45(2): 259-266.
[12] 刘建明, 鲁东明, 葛蓉. 基于全局优化的图像修复及其在GPU上实现[J]. J4, 2011, 45(2): 247-252.
[13] 战江涛,刘强,柴春雷. 基于三维模型与Gabor小波的人脸特征点跟踪方法[J]. J4, 2011, 45(1): 30-36.
[14] 梁文锋,项志宇. 鲁棒的PTZ摄像机目标跟踪算法[J]. J4, 2011, 45(1): 59-63.
[15] 宋坤坡, 夏顺仁, 徐清. 考虑小波系数相关性的超声图像降噪算法[J]. J4, 2010, 44(11): 2203-2208.