Bleeding simulation with stepless adaptive particles for surgical simulation systems

Area of Science:

• Virtual Reality
• Medical Simulation
• Computational Science

Background:

• Realistic bleeding simulation is vital for virtual surgery realism.
• High computational complexity of traditional particle methods hinders real-time performance.
• Existing methods lack sufficient visual fidelity and physical accuracy.

Purpose of the Study:

• To develop an adaptive-particle-based algorithm for realistic virtual surgery bleeding simulation.
• To improve visual realism while maintaining real-time performance and physical properties.
• To reduce computational complexity without sacrificing visual quality.

Main Methods:

• Integrated three modules using a Lagrangian particle method for high-fidelity simulation.
• Proposed a stepless adaptive particle algorithm adjusting mass/radius based on position.
• Incorporated particle repulsion for mass conservation and improved Smoothed Particle Hydrodynamics (SPH) for biomechanics.

Main Results:

• Achieved smoother bleeding surfaces, especially during topological changes like suction.
• Demonstrated stepless variations in particle radius through particle tracking.
• Validated suitability for various wound types and virtual surgical applications.

Conclusions:

• The proposed adaptive-particle algorithm significantly enhances bleeding simulation realism in virtual surgery.
• The method balances visual fidelity with computational efficiency for real-time applications.
• This approach offers a robust solution for simulating bleeding effects across diverse surgical scenarios.