CASIA OpenIR  > 09年以前成果
fMRI time series analysis based on stationary wavelet and spectrum analysis
Zhi Lianhe; Zhao Xia; Shan Baoci; et al.
Source PublicationPROGRESS IN NATURAL SCIENCE
2006-11-01
Volume16Issue:11Pages:1171-1176
SubtypeArticle
AbstractThe low signal to noise ratio (SNR) of functional MRI (fMRI) prefers more sensitive data analysis methods. Based on stationary wavelet transform and spectrum analysis' a new method with high detective sensitivity was developed for analyzing fMRI time series' which does not require any prior assumption of the characteristics of noises. In the proposed method' every component of fMRI time series in the different time-frequency scales of stationary wavelet transform was discerned by the spectrum analysis' then the components from noises were removed using the stationary wavelet transform' finally the components of real brain activation were detected by cross-correlation analysis. The results obtained from both simulated and in vivo visual experiments illustrated that the proposed method has much higher sensitivity than the traditional cross-correlation method.
KeywordFmri Stationary Wavelet Transform Spectrum Analysis Data Analysis
WOS HeadingsScience & Technology ; Technology
WOS KeywordFUNCTIONAL MRI ; HUMAN BRAIN ; RESPONSES ; SIGNAL
Indexed BySCI
Language英语
WOS Research AreaMaterials Science ; Science & Technology - Other Topics
WOS SubjectMaterials Science, Multidisciplinary ; Multidisciplinary Sciences
WOS IDWOS:000243150800007
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9359
Collection09年以前成果
Corresponding AuthorZhi Lianhe
Recommended Citation
GB/T 7714
Zhi Lianhe,Zhao Xia,Shan Baoci,et al. fMRI time series analysis based on stationary wavelet and spectrum analysis[J]. PROGRESS IN NATURAL SCIENCE,2006,16(11):1171-1176.
APA Zhi Lianhe,Zhao Xia,Shan Baoci,&et al..(2006).fMRI time series analysis based on stationary wavelet and spectrum analysis.PROGRESS IN NATURAL SCIENCE,16(11),1171-1176.
MLA Zhi Lianhe,et al."fMRI time series analysis based on stationary wavelet and spectrum analysis".PROGRESS IN NATURAL SCIENCE 16.11(2006):1171-1176.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhi Lianhe]'s Articles
[Zhao Xia]'s Articles
[Shan Baoci]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhi Lianhe]'s Articles
[Zhao Xia]'s Articles
[Shan Baoci]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhi Lianhe]'s Articles
[Zhao Xia]'s Articles
[Shan Baoci]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.