Abstract
We present an open-source system, Fiberfox, for generating synthetic diffusion-weighted datasets. Fiberfox enables (1) definition of artificial white matter fibers, (2) signal generation from those fibers using multi-compartment modeling, and (3) simulation of magnetic resonance artifacts including Gibbs ringing, Nā2 ghosting and susceptibility distortions. With a comparative hardware phantom study we show that the synthetic datasets closely resemble real acquisitions. To demonstrate the relevance of Fiberfox for current research questions, we reveal the adverse effects of anisotropic voxels on the outcome of 11 different fiber tractography algorithms. Fiberfox is openly available and may find application in the validation and further development of diffusion-weighted image processing techniques such as super-resolution, denoising, tractography, diffusion modeling or artifact correction.
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Neher, P.F., Laun, F.B., Stieltjes, B., Maier-Hein, K.H. (2014). Fiberfox: An Extensible System for Generating Realistic White Matter Software Phantoms. 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_10
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DOI: https://doi.org/10.1007/978-3-319-02475-2_10
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