• DocumentCode
    3085276
  • Title

    Statistical finite element analysis

  • Author

    Khalaji, Iman ; Rahemifar, Kaamran ; Samani, Abbas

  • Author_Institution
    Electrical Engineering Department, University of Western Ontario, London, N6A5B9 Canada
  • fYear
    2008
  • fDate
    20-25 Aug. 2008
  • Firstpage
    5577
  • Lastpage
    5580
  • Abstract
    A novel technique is introduced for tissue deformation and stress analysis. Compared to the conventional Finite Element method, this technique is orders of magnitude faster and yet still very accurate. The proposed technique uses preprocessed data obtained from FE analyses of a number of similar objects in a Statistical Shape Model framework as described below. This technique takes advantage of the fact that the body organs have limited variability, especially in terms of their geometry. As such, it is well suited for calculating tissue displacements of body organs. The proposed technique can be applied in many biomedical applications such as image guided surgery, or virtual reality environment development where tissue behavior is simulated for training purposes.
  • Keywords
    Biological system modeling; Computational modeling; Deformable models; Finite element methods; Geometry; Medical simulation; Shape; Stress; Surgery; Virtual reality; Algorithms; Computer Simulation; Elastic Modulus; Finite Element Analysis; Models, Biological; Models, Statistical; Pattern Recognition, Automated; Viscera; Viscosity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
  • Conference_Location
    Vancouver, BC
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-1814-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2008.4650478
  • Filename
    4650478