• DocumentCode
    1740868
  • Title

    3D curves tracking and its application to cortical sulci detection

  • Author

    Renault, Christophe ; Desvignes, Michel ; Revenu, Marinette

  • Author_Institution
    GREYC, ISMRA, Caen, France
  • Volume
    2
  • fYear
    2000
  • fDate
    10-13 Sept. 2000
  • Firstpage
    491
  • Abstract
    Automatic labelling and identification of cerebral structure, such as cortical sulci, are useful in neurology, surgery planning, etc... In this paper, a method to detect the valley of the cortical sulci is presented. The aim of the method is to achieve the sulci medial surface. The method, applied on MRI data, is based on geometrical features (curvature) and doesn´t require accurate segmentation of the cerebral cortex. We use sub-voxel precision tracking. The minimum curvature vector in each point allows successive displacement along the valley of sulci. Partial derivatives provide the differential characteristics.
  • Keywords
    biomedical MRI; brain; feature extraction; image recognition; medical image processing; 3D curves tracking; MRI data; cortical sulci detection; curvature; differential characteristics; geometrical features; minimum curvature vector; partial derivatives; sub-voxel precision tracking; successive displacement; sulci medial surface; valley; Brain mapping; Cerebral cortex; Humans; Image segmentation; Labeling; Land use planning; Magnetic resonance imaging; Nervous system; Surface morphology; Surgery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2000. Proceedings. 2000 International Conference on
  • Conference_Location
    Vancouver, BC, Canada
  • ISSN
    1522-4880
  • Print_ISBN
    0-7803-6297-7
  • Type

    conf

  • DOI
    10.1109/ICIP.2000.899462
  • Filename
    899462