TY - GEN
T1 - SEMI-Supervised learning of brain functional networks
AU - Du, Yuhui
AU - Sui, Jing
AU - Yu, Qingbao
AU - He, Hao
AU - Calhoun, Vince D.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/7/29
Y1 - 2014/7/29
N2 - Identification of subject-specific brain functional networks of interest is of great importance in fMRI based brain network analysis. In this study, a novel method is proposed to identify subject-specific brain functional networks using a graph theory based semi-supervised learning technique by incorporating not only prior information of the network to be identified as similarly used in seed region based correlation analysis (SCA) but also background information, which leads to robust performance for fMRI data with low signal noise ratio (SNR). Comparison experiments on both simulated and real fMRI data demonstrate that our method is more robust and accurate for identification of known brain functional networks than SCA, blind independent component analysis (ICA), and clustering based methods including Ncut and Kmeans.
AB - Identification of subject-specific brain functional networks of interest is of great importance in fMRI based brain network analysis. In this study, a novel method is proposed to identify subject-specific brain functional networks using a graph theory based semi-supervised learning technique by incorporating not only prior information of the network to be identified as similarly used in seed region based correlation analysis (SCA) but also background information, which leads to robust performance for fMRI data with low signal noise ratio (SNR). Comparison experiments on both simulated and real fMRI data demonstrate that our method is more robust and accurate for identification of known brain functional networks than SCA, blind independent component analysis (ICA), and clustering based methods including Ncut and Kmeans.
KW - Brain functional network
KW - Clustering
KW - Independent component analysis
KW - Semi-supervised learning
UR - http://www.scopus.com/inward/record.url?scp=84927923999&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84927923999&partnerID=8YFLogxK
U2 - 10.1109/isbi.2014.6867794
DO - 10.1109/isbi.2014.6867794
M3 - Conference contribution
AN - SCOPUS:84927923999
T3 - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
SP - 1
EP - 4
BT - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Y2 - 29 April 2014 through 2 May 2014
ER -