Jadrian Miles1, David H. Laidlaw1
1Computer Science Department, Brown University, Providence, RI, United States
We present an easy-to-implement method for computing uncertainty in deterministic DTI tractography. The model is derived from Monte-Carlo simulation studies of the effect of diffusion-weighted image noise and Q-space sampling on streamline orientation variability. The result is a straightforward equation for the growth of uncertainty that is linear in the arc-length distance from a streamline seed point.
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