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
fDate :
June 28 2009-July 1 2009
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;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-3931-7
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2009.5193209