Simulation of soft tissue deformation under physiological motion based on complementary dynamic method

Area of Science:

• Computational biomechanics
• Medical simulation
• Soft tissue modeling

Background:

• Physiological motions significantly influence soft tissue deformation, impacting surgical procedure accuracy.
• Realistic surgical simulation requires accurate modeling of soft tissue deformation under physiological motion.
• Integrating physiological motions into existing soft tissue deformation models remains a challenge.

Purpose of the Study:

• To introduce a novel deformation model for animating soft tissue deformation under physiological motion.
• To enhance the realism and accuracy of virtual surgery simulations.
• To address the challenge of integrating physiological motions into soft tissue deformation models.

Main Methods:

• Developed a novel deformation model based on complementary dynamics.
• Incorporated the finite element method to characterize soft tissue elastic behavior.
• Utilized mathematical models of physiological motion, converting effects into mesh displacements.
• Calculated complementary displacements from inherent soft tissue dynamics.

Main Results:

• Simulated soft tissues exhibited physiological motion synchronized with arterial pressure, heartbeat, and respiration.
• The proposed method demonstrated stable performance compared to existing force-based methods.
• Accurate characterization of soft tissue elastic behavior was achieved.

Conclusions:

• The novel method effectively governs both elastic behaviors and physiological motions in soft tissue deformation.
• Achieved a high degree of realistic visualization for virtual surgery simulation.
• Provides a robust approach for enhancing the fidelity of surgical training tools.