• DocumentCode
    2497705
  • Title

    An Eigenvector-Based Corresponding Points Auto-Detection Algorithm for Non-Rigid Registration of CT Brain Images

  • Author

    Sun, Tao ; Li, Chuanfu ; Feng, Huanqing

  • Author_Institution
    Dept. of Electron. Sci. & Tech., Univ. of Sci. & Tech. of China, Hefei, China
  • fYear
    2009
  • fDate
    11-13 June 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    CT brain images have advantage on the detection of brain tumor and cerebral hemorrhage. To provide integrated scheme of computer-aided diagnosis of these diseases with CT images, the non-rigid registration of CT images should be researched. In this paper, we present an eigenvector-based corresponding point automatic detection for non-rigid registration of CT brain images. Geometrical moment is first constructed for each voxel, and subsequently standard deviation of geometrical moment is computed. Eigenvectors, based on standard deviation and edge strength, are used to automatically and exactly determine the corresponding landmark points on fixed image for the pre-labeled landmark points on moving image and vice versa. The experiments show that the eigenvector-based point match method is accurate. It will be incorporated in the semi-auto non-rigid registration scheme for the further research.
  • Keywords
    brain; computerised tomography; eigenvalues and eigenfunctions; image matching; image registration; medical image processing; neurophysiology; CT brain image; auto-detection algorithm; brain tumor detection; cerebral hemorrhage; computer-aided diagnosis; eigenvector-based corresponding point automatic detection; eigenvector-based point match method; geometrical moment; nonrigid registration; Biomedical imaging; Brain; Computed tomography; Hemorrhaging; Histograms; Hospitals; Image edge detection; Magnetic resonance imaging; Neoplasms; Sun;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2901-1
  • Electronic_ISBN
    978-1-4244-2902-8
  • Type

    conf

  • DOI
    10.1109/ICBBE.2009.5162318
  • Filename
    5162318