Abstract

We propose a novel method to simulate soft tissue deformation for virtual surgery applications. The method considers the mechanical properties of soft tissue, such as its viscoelasticity, nonlinearity and incompressibility; its speed, stability and accuracy also meet the requirements for a surgery simulator. Modifying the traditional equation for mass spring dampers (MSD) introduces nonlinearity and viscoelasticity into the calculation of elastic force. Then, the elastic force is used in the constraint projection step for naturally reducing constraint potential. The node position is enforced by the combined spring force and constraint conservative force through Newton's second law. We conduct a comparison study of conventional MSD and position-based dynamics for our new integrating method. Our approach enables stable, fast and large step simulation by freely controlling visual effects based on nonlinearity, viscoelasticity and incompressibility. We implement a laparoscopic cholecystectomy simulator to demonstrate the practicality of our method, in which liver and gallbladder deformation can be simulated in real time. Our method is an appropriate choice for the development of real-time virtual surgery applications.

Highlights

  • Surgery simulators can help novices become familiar with real surgical procedures without human loss

  • Similar to extended position-based dynamics (XPBD) [20], we introduce a Lagrange multiplier to decompose the force into its directional and scalar components

  • Viscoelasticity and other time-related characteristics are simulated based on mass spring dampers (MSD)

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Summary

Introduction

Surgery simulators can help novices become familiar with real surgical procedures without human loss. They enable scientific and repeatable training through visual rendering via software. Simulating the deformation of soft tissue is necessary for rendering three key aspects of a surgery simulator: the surgical environment, organs’ interactions with the manipulator and force feedback [2]. It is crucial to develop a stable and fast method with which to simulate the complex deformation behaviours of biological soft tissue in real time

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