An improved fast marching method and its application in Alzheimer's disease |
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| Authors: | Xiaojie Zhao Xiaotong Wen Jiahui Shen Hao Hong Li Yao |
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| Affiliation: | 1. College of Information Science and Technology, Beijing Normal University, , Beijing, China;2. Department of Biomedical Engineering, University of Florida, , Gainesville, FA;3. State Key Lab of Cognitive Neuroscience and Learning, Beijing Normal University, , Beijing, China |
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| Abstract: | Magnetic resonance diffusion tensor imaging (DTI) provides a noninvasive approach to characterize the fiber pathways in the human brain. Among the fiber tractography algorithms in DTI analysis, the fast marching (FM) method has been widely used in quantitatively analyzing the structural connectivity of the fibers and their changes. However, standard FM only considers the similarity and the principal direction information conveyed by two neighboring voxels. It may have poor tracking performance when image noise and fiber crossing are present. To solve this problem, we introduced an improved FM method employing a memory factor (MFFM) to better characterize the directionality of fiber propagation. Simulation showed that MFFM yields higher tracking accuracy, lower computational load, and better antinoise/crossing performance compared with standard FM. Finally, we applied MFFM to Alzheimer's disease (AD) DTI data to explore the impaired regional connectivity of fiber structure. The results augment the knowledge of the pathological alteration of white matter in AD. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 346–352, 2013 |
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| Keywords: | fast marching method memory factor fiber tractography Alzheimer's disease structural connectivity |
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