Parallelized collision detection with applications in virtual bone machining

Fast and precise collision detection for detailed and complex physiological structures

BACKGROUND AND OBJECTIVES

Virtual reality has been proved indispensable in computer-assisted surgery, especially for surgical planning, and simulation systems. Collision detection is an essential part of surgery simulators and its accuracy and computational efficiency play a decisive role in the fidelity of simulations. Nevertheless, current collision detection methods in surgical simulation and planning struggle to meet precise requirements, especially for detailed and complex physiological structures. To address this, the primary objective of this study was to develop a new algorithm that enables fast and precise collision detection to facilitate the improvement of the realism of virtual reality surgical procedures.

METHODS

The method consists of two main parts, bounding spheres formation and two-level collision detection. A specified surface subdivision method is devised to reduce the radius of basic bounding spheres formed by circumcenters of underlying triangles. The spheres are then clustered and adjusted to obtain a compact personalized hierarchy whose position is updated in real time during surgical simulation, followed by two-level collision detection. Triangular facets with collision potential through interaction between hierarchies and then accurate results are obtained by means of precise detection phase. The effectiveness of the algorithm was evaluated in various models and surgical scenarios and was compared with prior relevant implementations.

RESULTS

Results on multiple models demonstrated that the method can generate a personalized hierarchy with fewer and smaller bounding spheres for tight wrapping. Simulation experiments proved that the proposed approach is significantly superior to comparable methods under the premise of error-free detection, even for severe model-model collision.

CONCLUSIONS

The algorithm proposed through this study enables higher numerical efficiency and detection accuracy, which is capable of significantly enlarging the fidelity/realism of haptic simulators and surgical planning methods.

Deformation modeling based on mechanical properties of liver tissue for virtuanormal vectors of trianglesl surgical simulation

PURPOSE

In this paper, a method for rapidly constructing a virtual surgical simulation system is proposed. A deformation model based on the mechanical properties of the liver and a rapid collision detection between the surgical micro-instruments and the liver tissue are included in this method. The purpose of this work is to improve the accuracy and real time of particle model deformation interaction in virtual surgery system.

METHODS

Firstly, a finite element model is established based on the constitutive model parameters of liver tissue. According to the simulation results, a mathematical model of node displacement is established. Secondly, the virtual liver is established based on the fast model reconstruction method, and the virtual manipulator is controlled by Geomagic Touch manipulator. Based on the hybrid bounding box, a rapid collision detection process between the instrument and liver is realized and the proposed deformation method is used to simulate the deformation of liver tissue.

RESULTS

The simulation and experiment results show that the proposed deformation model can achieve high deformation interaction accuracy. The collision detection algorithm based on the hybrid bounding boxes can realize the collision between the liver and the instrument, and the established virtual surgical simulation system can simulate the liver tissue deformation in the case of small loading displacement.

CONCLUSIONS

The effectiveness of the collision detection algorithm and deformation model was verified by an established virtual surgery simulation system. The proposed rapid construction method of virtual surgical simulation is feasible.