Abstract
Soft tissue modelling plays a significant role in surgery simulation as well as surgical procedure planning and training. However, it is a challenging research task to satisfy both physical realism and real-time simulation for soft tissue deformation. The finite element method (FEM) is a representative strategy for modelling of soft tissue deformation with highly physical realism. However, it suffers from expensive computations, unable to meet the requirement of real-time simulation. This paper proposes a novel method by combining FEM with the Kalman filter for real-time and accurate modelling of soft tissue deformation. The novelty of this method is that soft tissue deformation is formulated as a filtering identification process to online estimate soft tissue deformation from local measurement of displacement. To construct the discrete system state equation for filtering estimation, soft tissue deformation is discretised based on elastic theory in the space domain by FEM and is further discretised in the time domain by using the Wilson- $\theta $ implicit integration to solve the dynamic equilibrium equation of FEM deformation modelling. Subsequently, a Kalman filter is developed for online estimation and analysis of soft tissue deformation according to local measurement of displacement. Interactive tool-tissue interaction with haptic feedback is also achieved for surgery simulation. The presented method significantly improves the computational performance of the traditional FEM, but still maintains a similar level of accuracy. It not only achieves the real-time performance, but also exhibits the similar deformation behaviours as the traditional FEM and enables the use of large time steps to improve the simulation efficiency.
Highlights
Soft tissue modelling is a key issue in surgery simulation as well as surgical procedure planning and training
This paper proposes a new Kalman filter (KF)-finite element method (FEM) for dynamic modelling and analysis of soft tissue deformation
It carries out soft tissue deformation with a filtering identification process to online estimate mechanical behaviours of soft tissues based on local measurement of displacement
Summary
Soft tissue modelling is a key issue in surgery simulation as well as surgical procedure planning and training. Rather than direct calculation of soft tissue deformation from FEM, which causes an expensive computational load, this method formulates FEM deformation of soft tissues as a filtering identification process to real-time estimate soft tissue behaviours based on local measurement data of displacement. It discretizes soft tissue deformation based on elastic theory in the space domain using FEM. The dynamic FEM model of soft tissue deformation is discretized in the time domain by the Wilson-θ implicit integration, and further transformed into a state space representation for filtering estimation. This paper provides comprehensive performance evaluation, including detailed quantitative analysis, in-depth simulation results and analysis on virtual human organs for surgery simulation, experimental verification and analysis, and haptic interaction with virtual human organs for surgical simulation
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