• DocumentCode
    3226692
  • Title

    Intelligent feature selection for model-based bone segmentation in digital radiographs

  • Author

    Goossen, A. ; Peters, Dirk ; Gernoth, T. ; Pralow, Thomas ; Grigat, Rolf-Rainer

  • Author_Institution
    Vision Syst. Dept., Hamburg Univ. of Technol., Hamburg, Germany
  • fYear
    2009
  • fDate
    4-7 Nov. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper we propose a method to enhance Active Shape Model based bone segmentation. One major weakness of the classic algorithm is the use of a single dedicated image feature. However to model the variation of image content along the object boundaries it is more suitable to use different features for different regions. We derive an automatic intelligent selection of these features and integrate it into the classic Active Shape Model segmentation. We evaluated the proposed algorithm on the task of delineating bone structures in more than 150 clinical radiographs of the lower extremity and achieve superior accuracy compared to previously published approaches.
  • Keywords
    bone; diagnostic radiography; feature extraction; image segmentation; medical image processing; Active Shape Model; digital radiograph; image feature; intelligent feature selection; model based bone segmentation; Active shape model; Biomedical measurements; Bones; Extremities; Image segmentation; Information technology; Orthopedic surgery; Principal component analysis; Radiography; Shafts; Active Shape Models; Bone Structure; Digital Radiography; Orthopedic Measurement; Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Applications in Biomedicine, 2009. ITAB 2009. 9th International Conference on
  • Conference_Location
    Larnaca
  • Print_ISBN
    978-1-4244-5379-5
  • Electronic_ISBN
    978-1-4244-5379-5
  • Type

    conf

  • DOI
    10.1109/ITAB.2009.5394325
  • Filename
    5394325