Real-time and authentic blood simulation for surgical training

Blood simulation is an important part in the virtual surgery training system. However, the huge computational complexity and authenticity of blood simulation is of great challenge to the surgical training system. In this paper, a simulation method based on GPU-accelerated is used for blood simulation in surgical training system. The grid method is used to divide the target area, create space grid domain, and search neighboring particles by neighboring grid. We solve the particle control equation and calculate the interaction between blood and solid by parallel computing architecture (CUDA) multi-threaded parallel acceleration technology, which greatly improve the operational efficiency and improve the real-time of training. In addition, an improved marching cube algorithm was used to render the surface of fluid, which improved the authenticity of surgical training. Experimental results show that the authenticity and flexibility of blood meet the simulation requirements during the surgical training when using our method. Furthermore, the speed of blood simulation was significantly improved comparing to the realization of CPU.