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J4  2012, Vol. 46 Issue (9): 1722-1728    DOI: 10.3785/j.issn.1008-973X.2012.09.027
    
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
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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.



Published: 01 September 2012
CLC:  TP 391.41  
Cite this article:

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.

URL:

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


基于吸引区域的多模态脑磁共振图像仿射配准

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.

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