• DocumentCode
    2118618
  • Title

    Statistic Model of the Spine in Three-Dimension Geometry

  • Author

    Dai Jun ; Yu Bin ; Wang Ying

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Xidian Univ., Xi´an, China
  • fYear
    2010
  • fDate
    24-26 Dec. 2010
  • Firstpage
    66
  • Lastpage
    70
  • Abstract
    The study of the statistic model of the spine in three-dimension (3-D) geometry aims to provide a scientific basis for the spine and vertebra related medical surgery. In this paper, we adopt the Active Sharpe Model (ASM) to build a spinal statistical model. That is, we first locate and mark the feature points of the three-dimensional reconstructed medical Computed Tomography images, so as to obtain the shape matrix of each spine sample. Second, we align and register the shape matrix in the sample set with Iterative Closest Point (ICP). Third, we train the samples with Principal Component Analysis (PCA) and build the spinal statistical model in 3-D geometry. Finally, we evaluate the proposed model.
  • Keywords
    bone; computerised tomography; geometry; image reconstruction; iterative methods; medical image processing; principal component analysis; surgery; 3-D geometry; active sharpe model; computed tomography images; iterative closest point; principal component analysis; shape matrix; spinal statistical model; three-dimension geometry; three-dimensional reconstructed medical images; vertebra related medical surgery; Active shape model; Computational modeling; Data models; Iterative closest point algorithm; Principal component analysis; Shape; Solid modeling; Active Shape Model; Principal Component Analysis; Spine; Three-dimensional Model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ISISE), 2010 International Symposium on
  • Conference_Location
    Shanghai
  • ISSN
    2160-1283
  • Print_ISBN
    978-1-61284-428-2
  • Type

    conf

  • DOI
    10.1109/ISISE.2010.84
  • Filename
    5945053