虚拟手术中基于可碰撞集的软组织自碰撞检测算法

Algorithm of soft tissue self-collision detection based on potentially colliding set for virtual surgery

快速精确的碰撞检测是保证手术仿真真实性的重要条件。由于虚拟手术仿真过程中的高复杂性和高计算性,使得现有的碰撞检测已经不能满足实时性与复杂性的要求,为此提出一种新的软组织自碰撞检测方法。该方法根据软组织的曲率提取可碰撞集,基本几何元素间的自碰撞仅在该可碰撞集中发生,基本几何元素相交检测采用基于特征检测的方法。通过试验表明,该方法不仅能有效地提高碰撞检测的速度,而且能对人体软组织进行相对精确的检测。

Fast and accurate detection of soft tissue self-collision is an important prerequisite technique for reality surgery simulations. The current collision detection technologies can not meet the real-time requirement due to its high complexity in virtual surgery simulation. The authors proposed a new approach to extract possible collision dataset based on the curvature of soft tissue. The self-collision detection was only processed on possible collision sets. In addition, the characteristic analysis was used in geometrical elementary tests between primitives. The experiments indicate that the proposed method can improve the performance and accuracy of collision detection.