Real-Time Nonlinear Finite Element Analysis for Surgical Simulation Using Graphics Processing Units

Abstract

Clinical employment of biomechanical modelling techniques in areas of medical image analysis and surgical simulation is often hindered by conflicting requirements for high fidelity in the modelling approach and high solution speeds. We report the development of techniques for high-speed nonlinear finite element (FE) analysis for surgical simulation. We employ a previously developed nonlinear total Lagrangian explicit FE formulation which offers significant computational advantages for soft tissue simulation. However, the key contribution of the work is the presentation of a fast graphics processing unit (GPU) solution scheme for the FE equations. To the best of our knowledge this represents the first GPU implementation of a nonlinear FE solver. We show that the present explicit FE scheme is well-suited to solution via highly parallel graphics hardware, and that even a midrange GPU allows significant solution speed gains (up to 16.4x) compared with equivalent CPU implementations. For the models tested the scheme allows real-time solution of models with up to 16000 tetrahedral elements. The use of GPUs for such purposes offers a cost-effective high-performance alternative to expensive multi-CPU machines, and may have important applications in medical image analysis and surgical simulation.