DocumentCode
2116270
Title
Multi-fiber reconstruction from DW-MRI using a continuous mixture of von Mises-Fisher distributions
Author
Kumar, Ritwik ; Barmpoutis, Angelos ; Vemuri, Baba C. ; Carney, Paul R. ; Mareci, Thomas H.
Author_Institution
Dept. of Comput. & Inf. Sci. & Eng., Univ. of Florida, Tampa, FL
fYear
2008
fDate
23-28 June 2008
Firstpage
1
Lastpage
8
Abstract
In this paper we propose a method for reconstructing the Diffusion Weighted Magnetic Resonance (DW-MR) signal at each lattice point using a novel continuous mixture 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.
Keywords
biomedical MRI; fibres; image reconstruction; medical image processing; DW-MRI; MR signal attenuation; diffusion weighted-magnetic resonance image; lattice point; multifiber reconstruction; von Mises-Fisher distribution; Attenuation; Diffusion tensor imaging; Distributed computing; Distribution functions; Fourier transforms; Linear systems; Magnetic field measurement; Signal resolution; Solid modeling; Tensile stress;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition Workshops, 2008. CVPRW '08. IEEE Computer Society Conference on
Conference_Location
Anchorage, AK
ISSN
2160-7508
Print_ISBN
978-1-4244-2339-2
Electronic_ISBN
2160-7508
Type
conf
DOI
10.1109/CVPRW.2008.4562991
Filename
4562991
Link To Document