Abstract
Tractography allows us to explore white matter connectivity in diffusion MR images of the brain. However, noise, artifacts and limited resolution introduce uncertainty into the results. We propose a statistical model that allows us to quantify and visualize the uncertainty of a neuronal pathway between any two fixed anatomical regions. Given a sample set of tract curves obtained via tractography, we use our statistical model to define a confidence region that exposes the location and magnitude of tract uncertainty. The approach is validated on both synthetic and real diffusion MR data and is shown to highlight uncertain regions that occur due to noise, fiber crossings, or pathology.
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CJB and GH were partially supported by NSERC and BGB by IODE Canada and the Government of Alberta.
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Brown, C.J., Booth, B.G., Hamarneh, G. (2014). Uncertainty in Tractography via Tract Confidence Regions. In: Schultz, T., Nedjati-Gilani, G., Venkataraman, A., O'Donnell, L., Panagiotaki, E. (eds) Computational Diffusion MRI and Brain Connectivity. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-02475-2_12
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DOI: https://doi.org/10.1007/978-3-319-02475-2_12
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