计算机应用 ›› 2017, Vol. 37 ›› Issue (6): 1793-1797.DOI: 10.11772/j.issn.1001-9081.2017.06.1793

• 计算机视觉与虚拟现实 • 上一篇    下一篇

基于一般线性模型的功能磁共振成像回归量正交化

戴和谱, 刘刚, 何妍妍   

  1. 上海电力学院 自动化工程学院, 上海 200090
  • 收稿日期:2016-11-25 修回日期:2016-12-23 出版日期:2017-06-10 发布日期:2017-06-14
  • 通讯作者: 刘刚
  • 作者简介:戴和谱(1989-),男,湖北黄冈人,硕士研究生,主要研究方向:医学图像处理;刘刚(1977-),男,山东聊城人,教授,博士,主要研究方向:图像配准与分割、模式识别、机器学习;何妍妍(1992-),女,浙江义乌人,硕士研究生,主要研究方向:医学图像处理。
  • 基金资助:
    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)。

Orthogonalization of regressors in functional magnetic resonance imaging based on general linear model

DAI Hepu, LIU Gang, HE Yanyan   

  1. College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China
  • Received:2016-11-25 Revised:2016-12-23 Online:2017-06-10 Published:2017-06-14
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61203224), the Innovation Program of Shanghai Municipal Education Commission (13YZ101).

摘要: 针对功能磁共振成像(fMRI)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fMRI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。

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

Abstract: Concerning the collinearity 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.

Key words: functional Magnetic Resonance Imaging (fMRI), collinearity, General Linear Model (GLM), orthogonalization, Functional magnetic resonance imaging of the brain Software Library (FSL)

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