DocumentCode
2720867
Title
Automatic cortical surface parcellation based on fiber density information
Author
Zhang, Degang ; Guo, Lei ; Li, Gang ; Nie, Jingxin ; Fan Deng ; Li, Kaiming ; Hu, Xintao ; Zhang, Tuo ; Jiang, Xi ; Zhu, Dajiang ; Zhao, Qun ; Liu, Tianming
Author_Institution
Sch. of Autom., Northwestern Polytech. Univ., Xi´´an, China
fYear
2010
fDate
14-17 April 2010
Firstpage
1133
Lastpage
1136
Abstract
It is widely believed that the structural connectivity of a brain region largely determines its function. High resolution Diffusion Tensor Imaging (DTI) is now able to image the axonal fibers in vivo and the DTI tractography result provides rich connectivity information. In this paper, a novel method is proposed to employ fiber density information for automatic cortical parcellation based on the premise that fibers connecting to the same cortical region should be within the same functional brain network and their aggregation on the cortex can define a functionally coherent region. This method consists of three steps. Firstly, the fiber density is calculated on the cortical surface. Secondly, a flow field is obtained by calculating the fiber density gradient and a flow field tracking method is utilized for cortical parcellation. Finally, an atlas-based warping method is used to label the parcellated regions. Our method was applied to parcellate and label the cortical surfaces of eight healthy brain DTI images, and interesting results are obtained. In addition, the labeled regions are used as ROIs to construct structural networks for different brains, and the graph properties of these networks are measured.
Keywords
biomedical MRI; brain; neurophysiology; DTI tractography; atlas-based warping method; automatic cortical parcellation; automatic cortical surface parcellation; axonal fibers; brain region; connectivity information; fiber density information; functional brain network; graph properties; high resolution diffusion tensor imaging; structural connectivity; Automation; Computer science; Diffusion tensor imaging; Flowcharts; Image reconstruction; Image resolution; In vivo; Joining processes; Physics; Surface reconstruction; Cortical surface parcellation; fiber density; structure network;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on
Conference_Location
Rotterdam
ISSN
1945-7928
Print_ISBN
978-1-4244-4125-9
Electronic_ISBN
1945-7928
Type
conf
DOI
10.1109/ISBI.2010.5490193
Filename
5490193
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