摘要
针对功能磁共振成像(f MRI)模型回归量之间存在共线性的问题,提出了一种正交化的方法。首先,确定感兴趣以及待正交的回归量;其次,从待正交回归量中减去与感兴趣回归量相关的部分,使模型中共线的回归量正交分解为相互独立的部分,以此来消除共线性的影响。此外,还讨论和分析了正交化对一般线性模型的影响。最后,分别使用一些合成数据和当前一个流行的f MRI数据分析软件包——脑功能磁共振图像软件包(FSL)进行实验。实验结果表明,正交化方法可以消除模型中的共线性,并且提高感兴趣回归量的显著性,从而实现准确的脑功能定位,可以应用于对脑的基础研究和临床治疗。
Concerning the coIlinearity problem between the regressors in functional Magnetic Resonance Imaging （fMRI） model, a method of orthogonalization was proposed. Firstly, the regressors of interest and the regressors to be orthogonalized were determined. Then, the related part with regressos of interest was removed from the regressors to be orthogonalized, and the collinear regressors of the model were orthogonally decomposed into independent parts to eliminate the effect of collinearity. The influence of orthogonalization on General Linear Model （GLM） was also discussed and analysed. Finally, the experiments were carried out through some synthetic data and a current popular fMRI data analysis software package -- Functional magnetic resonance imaging of the brain Software Library （FSL）. The experimental results show that, the method of orthogonalization can eliminate the collinearity in the model and improve the significance of the regressors of interest to achieve accurate brain functional localization. The proposed method of orthogonalization can be used for the -basic research and clinical treatment of brain.
出处
《计算机应用》
CSCD
北大核心
2017年第6期1793-1797,1802,共6页
journal of Computer Applications
基金
国家自然科学基金资助项目(61203224)
上海市教委科技创新项目(13YZ101)~~
关键词
功能磁共振成像
共线性
一般线性模型
正交化
脑功能磁共振图像软件包
functional Magnetic Resonance Imaging （fMRI）
collinearity
General Linear Model （GLM）
orthogonalization
Functional magnetic resonance imaging of the brain Software Library （FSL）
