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Abstract #1906

Predicting DTI Tractography Uncertainty from Diffusion-Weighted-Image Noise

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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