• DocumentCode
    1573690
  • Title

    Automated Detection and Segmentation of Diaphyseal Bone Fragments From Registered C-Arm Images for Long Bone Fracture Reduction

  • Author

    Zheng, Guoyan ; Dong, Xiao ; Zhang, Xuan ; Nolte, Lutz-Peter

  • Author_Institution
    MEM Res Center, Bern Univ.
  • fYear
    2006
  • Firstpage
    4361
  • Lastpage
    4364
  • Abstract
    Automated identification, pose and size estimation, and contour extraction of diaphyseal bone fragments can greatly improve the usability of a computer-assisted fluoroscopy-based navigation system for long bone fracture reduction. In this paper, a two step solution is proposed. The pose and size of a diaphyseal fragment are estimated through 3D morphable object fitting using a parametric cylinder model. The result of fragment identification is then fed to a region information based active contour model to extract the fragment contour. Experimental results show a promising accuracy and robustness of the proposed approach
  • Keywords
    biomechanics; bone; computer vision; diagnostic radiography; fracture; image morphing; image recognition; image segmentation; medical image processing; orthopaedics; surgery; 3D morphable object fitting; automated detection; automated identification; computer-assisted fluoroscopy; computer-assisted surgery; contour extraction; diaphyseal bone fragments; fluoroscopy; fragment identification; long bone fracture reduction; navigation system; orthopaedics; parametric cylinder model; pose estimation; registered C-arm images; segmentation; size estimation; Active contours; Bones; Computed tomography; Data mining; Image segmentation; Navigation; Orthopedic surgery; Shape; Usability; Yield estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7803-8741-4
  • Type

    conf

  • DOI
    10.1109/IEMBS.2005.1615431
  • Filename
    1615431