Abstract
We propose a general approach to the reconstruction of brain white matter geometry from diffusion-weighted data. This approach is based on an inverse problem framework. The optimal geometry corresponds to the lowest energy configuration of a spin glass. These spins represent pieces of fascicles that orient themselves according to diffusion data and interact in order to create low curvature fascicles. Simulated diffusion-weighted datasets corresponding to the crossing of two fascicle bundles are used to validate the method.
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Cointepas, Y., Poupon, C., Le Bihan, D., Mangin, JF. (2002). A Spin Glass Based Framework to Untangle Fiber Crossing in MR Diffusion Based Tracking. In: Dohi, T., Kikinis, R. (eds) Medical Image Computing and Computer-Assisted Intervention — MICCAI 2002. MICCAI 2002. Lecture Notes in Computer Science, vol 2488. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45786-0_59
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DOI: https://doi.org/10.1007/3-540-45786-0_59
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