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Abstract #4760

Accurate Estimation of Fiber Orientations in the Mouse Brain from Diffusion MRI Signals: Learning from Histological Ground Truth

Zifei Liang1, Tanzil Mahmud Arefin1, Choong Heon Lee1, and Jiangyang Zhang1
1NYU Langone Health, New York, NY, United States


Although dMRI tractograophy has been successfully used to examine brain connectivity, its limitation, mainly in specificity, has also been reported. In this study, we generated a comprehensive mouse brain streamline database based on 2700+ viral tracer data from Allen Institute. The database was used as a ground truth to train a deep learning network to estimate fiber orientations from diffusion MRI data of the mouse brain. Compared to conventional methods, the deep learning network provided more accurate estimation of fiber orientation leading to improved tractography.

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