ICA算法在fMRI中的应用  

Application of the ICA Algorithm in fMRI

作　　者：公昱文[1] 张桂芸[1] 马洪芝[1] 

机构地区：[1]天津师范大学计算机与信息工程学院,天津300387

出　　处：《计算机工程与科学》2008年第10期37-39,共3页Computer Engineering & Science

基　　金：天津市教委资助项目(20071328);天津师范大学大博士基金资助项目(52LX17)

摘　　要：独立分量分析(ICA)是信号处理领域新近发展起来的一种很有应用前景的方法,而脑功能磁共振(fMRI)信号的有效分离与识别是一个正在研究和实验之中的技术领域。近年来,ICA已被成功地应用于fMRI数据的处理,成为分析fMRI数据的一种很有效的方法。本文介绍了ICA在分析fMRI数据方面的应用,以及多种ICA算法在fMRI信号盲源分离中的应用,分析了三种算法的问题,给出了本人对此研究的展望。ICA is the application of very promising methods in the field of signal processing. While the effective separation and identification of the fMRI signals is a technical field which is being studied and experimented. In recent years, ICA has been successfully used in the fMRI data processing. It has become a very effective way of analyzing the fMRI data. The paper introduces the application of ICA both in the analysis of the fMRI data and a variety of algorithms in the blind source separation of the fMRI signals. It also analyzes the problems existing in three algorithms, and presents the prospect of research in this field.

关 键 词：ICA FMRI 空间独立分量分析算法Orth-Infomax算法 Group ICA算法 

分 类 号：TN911.7[电子电信—通信与信息系统]