Abstract
We propose a framework for estimating fiber fields in the heart from arbitrarily spaced diffusion weighted MRI. The approach is based on a parametric and space-dependent mathematical representation of the helix angles across the heart, leading to a semi-analytical formula of the diffusion tensor, without any particular assumption on the ventricular shape. Then, by solving an nonlinear inverse problem, the degrees of freedom of the model can be estimated from measured diffusion weighted data. We illustrate the methodology using synthetic data and compare it with previously reported fiber reconstruction techniques.
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Acknowledgements
The results presented in this article are part of the Advanced Cardiac Mechanics Emulator, an initiative supported by the Institute for Advanced Study (TU München). This support is gratefully acknowledged. We also thank Radomír Chabiniok and Jack Harmer (King’s College London) for the valuable discussions.
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Nagler, A., Bertoglio, C., Stoeck, C.T., Kozerke, S., Wall, W.A. (2015). Cardiac Fibers Estimation from Arbitrarily Spaced Diffusion Weighted MRI. In: van Assen, H., Bovendeerd, P., Delhaas, T. (eds) Functional Imaging and Modeling of the Heart. FIMH 2015. Lecture Notes in Computer Science(), vol 9126. Springer, Cham. https://doi.org/10.1007/978-3-319-20309-6_23
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DOI: https://doi.org/10.1007/978-3-319-20309-6_23
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