• DocumentCode
    2807446
  • Title

    Registration of contours of brain structures through a heat-kernel representation of shape

  • Author

    Bates, Jonathan ; Wang, Ying ; Liu, Xiuwen ; Mio, Washington

  • Author_Institution
    Dept. of Math., Florida State Univ., Tallahasse, FL, USA
  • fYear
    2009
  • fDate
    June 28 2009-July 1 2009
  • Firstpage
    943
  • Lastpage
    946
  • Abstract
    We develop an algorithm for the registration of surfaces representing the contours of various subcortical structures of the human brain. We employ a scale-space representation of shape based on the heat kernel, which only depends on the intrinsic geometry of the surfaces. The multi-scale representation is used in conjunction with the non-linear Iterative Closest Point algorithm based on thin-plate-spline warps to establish point correspondences between shapes. The method is applied to the registration of the contours of four subcortical structures: the hippocampus, caudate nucleus, putamen, and third ventricle.
  • Keywords
    brain; image registration; iterative methods; medical image processing; splines (mathematics); caudate nucleus; heat-kernel shape representation; hippocampus; human brain; nonlinear iterative closest point algorithm; putamen; scale-space representation; subcortical structure contour; surface registration; thin-plate-spline; third ventricle; Brain; Eigenvalues and eigenfunctions; Geometry; Hippocampus; Iterative algorithms; Iterative closest point algorithm; Kernel; Mathematics; Shape; Surface morphology; Shape registration; heat-kernel representation; spectral representation; surface registration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
  • Conference_Location
    Boston, MA
  • ISSN
    1945-7928
  • Print_ISBN
    978-1-4244-3931-7
  • Electronic_ISBN
    1945-7928
  • Type

    conf

  • DOI
    10.1109/ISBI.2009.5193209
  • Filename
    5193209