Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100083, China.
Rossum Robot Co., Ltd, Beijing, China.
Comput Methods Programs Biomed. 2023 Oct;240:107707. doi: 10.1016/j.cmpb.2023.107707. Epub 2023 Jul 3.
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.
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 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.
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.
虚拟现实在计算机辅助手术中已被证明不可或缺，尤其是在手术规划和模拟系统中。碰撞检测是手术模拟器的重要组成部分，其准确性和计算效率对模拟的逼真度起着决定性作用。然而，当前手术模拟和规划中的碰撞检测方法难以满足精确要求，尤其是对于详细和复杂的生理结构。为此，本研究的主要目的是开发一种新的算法，实现快速准确的碰撞检测，以提高虚拟现实手术过程的真实感。
该方法由两部分组成，即包围球形成和两级碰撞检测。设计了一种指定的曲面细分方法，以减小由底层三角形外接圆形成的基本包围球的半径。然后对这些球进行聚类和调整，以获得一个紧凑的个性化层次结构，该层次结构的位置在手术模拟过程中实时更新，然后进行两级碰撞检测。通过层次结构之间的交互形成具有碰撞潜力的三角面片，然后通过精确检测阶段获得准确的结果。该算法在多种模型和手术场景中进行了评估，并与先前的相关实现进行了比较。
在多个模型上的结果表明，该方法可以生成一个具有较少和较小包围球的个性化层次结构，实现紧密包裹。模拟实验证明，在错误检测的前提下，与可比方法相比，所提出的方法具有显著优势，即使在严重的模型-模型碰撞情况下也是如此。
通过本研究提出的算法能够提高数值效率和检测精度，从而显著扩大触觉模拟器和手术规划方法的逼真度/真实感。
