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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Multi-fiber reconstruction from DW-MRI using a continuous mixture of von Mises-Fisher distributions
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Ritwik Kumar, Department of Computer and Information Science and Engineering, University of Florida, USA
Angelos Barmpoutis, Department of Computer and Information Science and Engineering, University of Florida, USA
Baba C. Vemuri, Department of Computer and Information Science and Engineering, University of Florida, USA
Paul R. Carney, Department of Pediatrics, University of Florida, USA
Thomas H. Mareci, Department of Biochemistry and Molecular Biology, University of Florida, USA
In this paper we propose a method for reconstructing the Diffusion Weighted Magnetic Resonance (DW-MR) signal at each lattice point using a novel continuousmixture of von Mises-Fisher distribution functions. Unlike most existing methods, neither does this model assume a fixed functional form for the MR signal attenuation (e.g. 2nd or 4th order tensor) nor does it arbitrarily fix important mixture parameters like the number of components. We show that this continuous mixture has a closed form expression and leads to a linear system which can be easily solved. Through extensive experimentation with synthetic data we show that this technique outperforms various other state-of-the-art techniques in resolving fiber crossings. Finally, we demonstrate the effectiveness of this method using real DW-MRI data from rat brain and optic chiasm.
Citation:
Ritwik Kumar, Angelos Barmpoutis, Baba C. Vemuri, Paul R. Carney, Thomas H. Mareci, "Multi-fiber reconstruction from DW-MRI using a continuous mixture of von Mises-Fisher distributions," cvprw, pp.1-8, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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