TY - GEN
T1 - Deriving ADHD biomarkers with sparse coding based network analysis
AU - Ge, Fangfei
AU - Lv, Jinglei
AU - Hu, Xintao
AU - Ge, Bao
AU - Guo, Lei
AU - Han, Junwei
AU - Liu, Tianming
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/7/21
Y1 - 2015/7/21
N2 - Sparse coding has been increasingly used to explore brain networks using functional magnetic resonance imaging (fMRI). However, modeling and comparing brain network based on sparse coding is still challenging, especially in clinical applications. In this study, we propose a novel temporal sparse coding method to identify functional connectivity biomarkers in patients with Attention-Deficit/Hyperactivity Disorder (ADHD). Specifically, a group-wise temporal sparse coding method was proposed to localize corresponding brain regions of interest (ROIs) in rsfMRI data. The localized common ROIs were then used as brain network nodes for further functional connectivity analysis. By using a publicly available ADHD-200 dataset, we demonstrated that our method can identify functional connectivity biomarkers with improved performance in patient-healthy controls classification compared with the widely used independent component analysis (ICA).
AB - Sparse coding has been increasingly used to explore brain networks using functional magnetic resonance imaging (fMRI). However, modeling and comparing brain network based on sparse coding is still challenging, especially in clinical applications. In this study, we propose a novel temporal sparse coding method to identify functional connectivity biomarkers in patients with Attention-Deficit/Hyperactivity Disorder (ADHD). Specifically, a group-wise temporal sparse coding method was proposed to localize corresponding brain regions of interest (ROIs) in rsfMRI data. The localized common ROIs were then used as brain network nodes for further functional connectivity analysis. By using a publicly available ADHD-200 dataset, we demonstrated that our method can identify functional connectivity biomarkers with improved performance in patient-healthy controls classification compared with the widely used independent component analysis (ICA).
KW - ADHD
KW - biomarkers
KW - functional connectivity
KW - resting-state fMRI
KW - temporal sparse coding
UR - http://www.scopus.com/inward/record.url?scp=84944318835&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2015.7163807
DO - 10.1109/ISBI.2015.7163807
M3 - 会议稿件
AN - SCOPUS:84944318835
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 22
EP - 25
BT - 2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015
PB - IEEE Computer Society
T2 - 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015
Y2 - 16 April 2015 through 19 April 2015
ER -