AUTOMATIC CORTICAL SURFACE PARCELLATION BASED ON FIBER DENSITY INFORMATION

被引:11
|
作者
Zhang, Degang [1 ,3 ,4 ]
Guo, Lei [1 ]
Li, Gang [1 ]
Nie, Jingxin [1 ]
Deng, Fan [2 ,3 ]
Li, Kaiming [1 ,2 ,3 ]
Hu, Xintao [1 ]
Zhang, Tuo [1 ]
Jiang, Xi [1 ]
Zhu, Dajiang [2 ,3 ]
Zhao, Qun [3 ,4 ]
Liu, Tianming [2 ,3 ]
机构
[1] Northwestern Polytech Univ, Sch Automat, Xian 710072, Peoples R China
[2] Univ Georgia, Dept Comp Sci, Athens, GA 30602 USA
[3] Univ Georgia, Bioimaging Res Ctr, Athens, GA 30602 USA
[4] Univ Georgia, Dept Phys, Athens, GA 30602 USA
关键词
Cortical surface parcellation; fiber density; structure network; CONNECTIVITY-BASED PARCELLATION; HUMAN THALAMUS; CORTEX; REGISTRATION; REGIONS; FLOW; MRI;
D O I
10.1109/ISBI.2010.5490193
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
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.
引用
收藏
页码:1133 / 1136
页数:4
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