DocumentCode :
2464006
Title :
Exploiting peak anisotropy for tracking through complex structures
Author :
Seunarine, Kiran K. ; Cook, P.A. ; Hall, M.G. ; Embleton, K.V. ; Parker, G.J.M. ; Alexander, Daniel C.
Author_Institution :
Univ. Coll. London, London
fYear :
2007
fDate :
14-21 Oct. 2007
Firstpage :
1
Lastpage :
8
Abstract :
This work shows that multi-fibre reconstruction techniques, such as Persistent Angular Structure (PAS) MRI or QBall Imaging, provide much more information than just discrete fibre orientations, which is all that previous tractography algorithms exploit from them. We show that the shapes of the peaks of the functions output by multiple-fibre reconstruction algorithms reflect the underlying distribution of fibres. Furthermore, we show how to exploit this extra information to improve Probabilistic Index of Connectivity (PICo) tractography. The method uses the Bingham distribution to model the uncertainty in fibre-orientation estimates obtained from peaks in the PAS or QBall Orientation Distribution Function (ODF). The Bingham model captures anisotropy in the uncertainty, allowing the method to track through fanning and bending structures, which previous methods do not recover reliably. We devise a new calibration procedure to construct a mapping from peak shape to Bingham parameters. We test the accuracy of the calibration using a bootstrap experiment. Finally, we show that exploiting the peak shape in this way can provide improved PICo tractography results.
Keywords :
biomedical MRI; image reconstruction; medical image processing; probability; Bingham parameters; MRI; bending structures; bootstrap experiment; complex structure tracking; discrete fibre orientations; multifibre reconstruction; orientation distribution function; peak anisotropy; persistent angular structure; probabilistic index of connectivity; tractography algorithms; Anisotropic magnetoresistance; Biomedical imaging; Calibration; Diffusion tensor imaging; Image reconstruction; Magnetic resonance imaging; Reconstruction algorithms; Shape; Streaming media; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
Conference_Location :
Rio de Janeiro
ISSN :
1550-5499
Print_ISBN :
978-1-4244-1630-1
Electronic_ISBN :
1550-5499
Type :
conf
DOI :
10.1109/ICCV.2007.4409168
Filename :
4409168
Link To Document :
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