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一种磁共振脑功能成像的头部移动校正方法
引用本文:汪和生,王涛,冯焕清,吴端.一种磁共振脑功能成像的头部移动校正方法[J].中国科学技术大学学报,2002,32(5):573-578.
作者姓名:汪和生  王涛  冯焕清  吴端
作者单位:1. 中国科学技术大学电子科技系,安徽合肥,230026
2. 安徽省菲特科技有限公司,安徽合肥,230061
摘    要:在磁共振脑功能成像(functional magnetic resonance imaging,fMRI)试验中,头部很小的移动就会对试验结果产生不良影响,因此在对数据统计分析之前要求进行移动校正。本文利用LMF(levenberg-mrquardt-fletcher)算法极小化参考图像和校正图像之间的残差平方和自动校正fMRI图像,根据多分辨率金字塔结构由粗到细地搜索最优解,既可以较快的收敛,又可以考虑较大的移动。

关 键 词:头部移动校正  磁共振脑功能成像  LMF非线性最小二乘法  金字塔结构  残差平方  fMRI图像
文章编号:0253-2778(2002)05-0573-06

An Algorithm for Correcting Head Motion in Functional Magnetic Resonance Imaging
WANG He sheng ,WANG Tao ,FENG Huan qing ,WU Duan.An Algorithm for Correcting Head Motion in Functional Magnetic Resonance Imaging[J].Journal of University of Science and Technology of China,2002,32(5):573-578.
Authors:WANG He sheng  WANG Tao  FENG Huan qing  WU Duan
Institution:WANG He sheng 1,WANG Tao 1,FENG Huan qing 1,WU Duan 2
Abstract:Even rather small head motion during brain functional magnetic resonance imaging (fMRI) may influence the results of experiment. Therefore, it is necessary to correct head motion before doing statistical analysis for image data. A method is presented in the paper that minimizes the mean square difference of intensities between a reference and the images being corrected using LMF algorithm for non linear least square optimization. And multiresloution pyramid implementation serving coarse to fine minimization enables a fast convergence and a good performance in case of large displacements.
Keywords:fMRI  LMF non  linear least  square optimization  pyramidical structure
本文献已被 CNKI 维普 万方数据 等数据库收录!
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