• Title of article

    An electromechanical based deformable model for soft tissue simulation

  • Author/Authors

    Zhong، نويسنده , , Yongmin and Shirinzadeh، نويسنده , , Bijan and Smith، نويسنده , , Julian and Gu، نويسنده , , Chengfan، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2009
  • Pages
    14
  • From page
    275
  • To page
    288
  • Abstract
    SummaryObjective issue deformation is of great importance to surgery simulation. Although a significant amount of research efforts have been dedicated to simulating the behaviours of soft tissues, modelling of soft tissue deformation is still a challenging problem. This paper presents a new deformable model for simulation of soft tissue deformation from the electromechanical viewpoint of soft tissues. s and material issue deformation is formulated as a reaction–diffusion process coupled with a mechanical load. The mechanical load applied to a soft tissue to cause a deformation is incorporated into the reaction–diffusion system, and consequently distributed among mass points of the soft tissue. Reaction–diffusion of mechanical load and non-rigid mechanics of motion are combined to govern the simulation dynamics of soft tissue deformation. s roved reaction–diffusion model is developed to describe the distribution of the mechanical load in soft tissues. A three-layer artificial cellular neural network is constructed to solve the reaction–diffusion model for real-time simulation of soft tissue deformation. A gradient based method is established to derive internal forces from the distribution of the mechanical load. Integration with a haptic device has also been achieved to simulate soft tissue deformation with haptic feedback. sions oposed methodology does not only predict the typical behaviours of living tissues, but it also accepts both local and large-range deformations. It also accommodates isotropic, anisotropic and inhomogeneous deformations by simple modification of diffusion coefficients.
  • Keywords
    reaction–diffusion , Artificial neural network , Soft tissue deformation , Haptic feedback , Surgery simulation
  • Journal title
    Artificial Intelligence In Medicine
  • Serial Year
    2009
  • Journal title
    Artificial Intelligence In Medicine
  • Record number

    1836853