Abstract
One overarching challenge of clinical magnetic resonance imaging (MRI) is to quantify tissue structure at the cellular scale of micrometers, based on an MRI acquisition with a millimeter resolution. Diffusion MRI (dMRI) provides the strongest sensitivity to the cellular structure. However, interpreting dMRI measurements has remained a highly ill-posed inverse problem. Here we propose a framework that resolves the above challenge for human white matter fibers, by unifying intra-voxel mesoscopic modeling with global fiber tractography. Our algorithm is based on a Simulated Annealing approach which simultaneously optimizes diffusion parameters and fiber locations. Each fiber carries its individual set of diffusion parameters which allows to link them by their structural relationships.
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Keywords
- Magnetic Resonance Imaging Acquisition
- Simulated Annealing Approach
- Clinical Magnetic Resonance Imaging
- Reversible Jump Monte Carlo Markov Chain
- Fiber Tractography
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Reisert, M., Kiselev, V.G., Dihtal, B., Kellner, E., Novikov, D.S. (2014). MesoFT: Unifying Diffusion Modelling and Fiber Tracking. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014. MICCAI 2014. Lecture Notes in Computer Science, vol 8675. Springer, Cham. https://doi.org/10.1007/978-3-319-10443-0_26
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DOI: https://doi.org/10.1007/978-3-319-10443-0_26
Publisher Name: Springer, Cham
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