thesis

Real-time simulation of soft tissue deformation for surgical simulation

Abstract

Surgical simulation plays an important role in the training, planning and evaluation of many surgical procedures. It requires realistic and real-time simulation of soft tissue deformation under interaction with surgical tools. However, it is challenging to satisfy both of these conflicting requirements. On one hand, biological soft tissues are complex in terms of material compositions, structural formations, and mechanical behaviours, resulting in nonlinear deformation characteristics under an external load. Due to the involvement of both material and geometric nonlinearities, the use of nonlinear elasticity causes a highly expensive computational load, leading to the difficulty to achieve the real-time computational performance required by surgical simulation. On the other hand, in order to satisfy the real-time computational requirement, most of the existing methods are mainly based on linear elasticity under the assumptions of small deformation and homogeneity to describe deformation of soft tissues. Such simplifications allow reduced runtime computation; however, they are inadequate for modelling nonlinear material properties such as anisotropy, heterogeneity and large deformation of soft tissues. In general, the two conflicting requirements of surgical simulation raise immense complexity in modelling of soft tissue deformation. This thesis focuses on establishment of new methodologies for modelling of soft tissue deformation for surgical simulation. Due to geometric and material nonlinearities in soft tissue deformation, the existing methods have only limited capabilities in achieving nonlinear soft tissue deformation in real-time. In this thesis, the main focus is devoted to the real-time and realistic modelling of nonlinear soft tissue deformation for surgical simulation. New methodologies, namely new ChainMail algorithms, energy propagation method, and energy balance method, are proposed to address soft tissue deformation. Results demonstrate that the proposed methods can simulate the typical soft tissue mechanical properties, accommodate isotropic and homogeneous, anisotropic and heterogeneous materials, handle incompressibility and viscoelastic behaviours, conserve system energy, and achieve realistic, real-time and stable deformation. In the future, it is projected to extend the proposed methodologies to handle surgical operations, such as cutting, joining and suturing, for topology changes occurred in surgical simulation

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