Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
Fiber-centered analysis of brain connectivities using DTI and resting state FMRI data
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
Activated fibers: fiber-centered activation detection in task-based FMRI
IPMI'11 Proceedings of the 22nd international conference on Information processing in medical imaging
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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 parcell ate 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.