Performance evaluation of anisotropic diffusion simulation based tractography on phantom images

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Abstract

White matter tractography using diffusion tensor MR images is a promising method for estimating the pathways of white matter tracts in the human brain. The success of this method ultimately depends upon the accuracy of the white matter tractography algorithms. In this study, a central database of simulated common fiber tract trajectories was used to investigate the impact of SNR, tensor anisotropy, and diffusion tensor encoding directions on the accuracy of our fiber tracking method. The accuracy was assessed in six kinds of tracts and tract geometrics with divergence properties. In general the tract dispersion increases with distance and decreases with SNR and anisotropy. The tract orientation with respect to the encoding scheme also influences tract dispersion. Divergent tract geometries enhance tract dispersion, whereas convergent tract geometries reduce dispersion.

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