• DocumentCode
    3380292
  • Title

    A Deformable Statistical Shape Model Applied to Three-Dimensional Lumbar Vertebra Images

  • Author

    Ling, Jian ; Bartels, Keith ; Nicolella, Daniel

  • Author_Institution
    Southwest Res. Inst., San Antonio, TX
  • fYear
    2008
  • fDate
    24-26 March 2008
  • Firstpage
    133
  • Lastpage
    136
  • Abstract
    A surface morphing technique utilizing the generalized gradient vector flow (GGVF) method was implemented and tested. The surface morphing results in a homeomorphic deformation of a reference surface onto individual members of a data set. Internal and external forces that drive the surface morphing result in correspondences between the parameterized surfaces. Principal component analysis was used to form a statistical shape model from the resulting surfaces. Three dimensional LI-lumbar vertebral images were used to demonstrate the algorithm. Volume image preprocessing and segmentation is described as well.
  • Keywords
    bone; image morphing; image segmentation; medical image processing; orthopaedics; principal component analysis; deformable statistical shape model; generalized gradient vector flow method; homeomorphic deformation; principal component analysis; surface morphing technique; three-dimensional lumbar vertebra images; volume image preprocessing; volume image segmentation; Computed tomography; Deformable models; Humans; Image segmentation; Isosurfaces; Mathematical model; Shape; Spine; Surface morphology; X-ray imaging; 3D Medical Imaging; Lumbar Vertebra; Statistical Shape Model; Surface Morphing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Analysis and Interpretation, 2008. SSIAI 2008. IEEE Southwest Symposium on
  • Conference_Location
    Santa Fe, NM
  • Print_ISBN
    978-1-4244-2296-8
  • Electronic_ISBN
    978-1-4244-2297-5
  • Type

    conf

  • DOI
    10.1109/SSIAI.2008.4512303
  • Filename
    4512303