• 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