Abstract #4530
A probabilistic method for unbiased longitudinal tractography with application to Huntington's disease
Anastasia Yendiki 1 , Martin Reuter 1 , Paul Wilkens 1 , Herminia Diana Rosas 1 , and Bruce Fischl 1,2
1
HMS/MGH/MIT Athinoula A. Martinos Center for
Biomedical Imaging, Charlestown, MA, United States,
2
MIT
Computer Science and Artificial Intelligence Laboratory,
Cambridge, MA, United States
We propose a probabilistic method for reconstructing
white-matter pathways from longitudinal diffusion MRI
data. We model the posterior probability of a pathway
given a subject's full longitudinal data set, including
diffusion and structural images from all time points.
Our method is unbiased, making no assumptions on the
direction of longitudinal change. By design, it allows
longitudinal analysis of anisotropy and diffusivity
measures to be performed as a function of position along
the trajectory of a tract. We demonstrate that our
longitudinal tractography improves both specificity and
sensitivity compared to the conventional approach of
performing tractography in each time point
independently.
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