TY - GEN
T1 - Construction of multi-scale brain networks via DICCCOL landmarks
AU - Ge, Bao
AU - Guo, Lei
AU - Zhang, Tuo
AU - Zhu, Dajiang
AU - Hu, Xintao
AU - Han, Junwei
AU - Liu, Tianming
PY - 2013
Y1 - 2013
N2 - Mapping human brain networks has gained significant interest in the last few years, as it offers novel perspectives on the brain structure and function. However, most previous approaches were dedicated to a single resolution or scale of brain network, though the brain networks are multi-scale in nature. This paper presents a novel approach to constructing multi-scale structural brain networks from DTI images via multi-scale spectral clustering of our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess structural and functional correspondences across subjects, the constructed multi-scale networks also have intrinsically-established correspondences across different brains, which is a prominent feature of this network construction method. Experimental results demonstrated that the proposed method can generated consistent and common structural brain networks, which will lay down the foundation for many other network-based neuroimaging analyses in the future.
AB - Mapping human brain networks has gained significant interest in the last few years, as it offers novel perspectives on the brain structure and function. However, most previous approaches were dedicated to a single resolution or scale of brain network, though the brain networks are multi-scale in nature. This paper presents a novel approach to constructing multi-scale structural brain networks from DTI images via multi-scale spectral clustering of our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess structural and functional correspondences across subjects, the constructed multi-scale networks also have intrinsically-established correspondences across different brains, which is a prominent feature of this network construction method. Experimental results demonstrated that the proposed method can generated consistent and common structural brain networks, which will lay down the foundation for many other network-based neuroimaging analyses in the future.
KW - DICCCOL
KW - DTI
KW - multi-scale brain networks
UR - http://www.scopus.com/inward/record.url?scp=84881646769&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2013.6556566
DO - 10.1109/ISBI.2013.6556566
M3 - 会议稿件
AN - SCOPUS:84881646769
SN - 9781467364546
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 680
EP - 683
BT - ISBI 2013 - 2013 IEEE 10th International Symposium on Biomedical Imaging
T2 - 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013
Y2 - 7 April 2013 through 11 April 2013
ER -