Abstract
Diffusional Kurtosis Imaging (DKI) is able to capture non-Gaussian diffusion and has become a popular complement to the more traditional Diffusion Tensor Imaging (DTI). In this paper, we demonstrate how strongly the presence of fiber crossings and the exact crossing angle affect measures from diffusional kurtosis, limiting their interpretability as indicators of tissue microstructure. We alleviate this limitation by modeling fiber crossings with a mixture of cylindrically symmetric kurtosis models. Based on results on simulated and on real-world data, we conclude that explicitly including crossing geometry in kurtosis models leads to parameters that are more specific to other aspects of tissue microstructure, such as scale and homogeneity.
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Keywords
- Fractional Anisotropy
- Diffusion Tensor Image
- Bayesian Information Criterion
- Superior Longitudinal Fasciculus
- Fiber Crossing
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Ankele, M., Schultz, T. (2015). Quantifying Microstructure in Fiber Crossings with Diffusional Kurtosis. In: Navab, N., Hornegger, J., Wells, W., Frangi, A. (eds) Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science(), vol 9349. Springer, Cham. https://doi.org/10.1007/978-3-319-24553-9_19
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DOI: https://doi.org/10.1007/978-3-319-24553-9_19
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