Calibration of mass spring models for organ simulations

The two main categories of deformable models used in surgical simulators are Mass Spring Models (MSM) and Finite Element Models (FEM). Mass spring models are often preferred due to their simplicity and low computational cost and because they allow to perform topology changes on the modeled body without significant computational overhead. The principal drawback of the mass spring model is the need of complex calibration procedure since they don´t have a clear physical meaning. In this paper we propose a new method to calibrate mass spring models. Our method uses CAT data to identify mass values and deformation measures to define elastic coefficient and damping ratio for the springs of the model. Spring parameters are obtained through a genetic algorithm that minimizes the difference between the model and the measured behavior. The algorithm we developed to compute the masses was tested with medical CAT data whereas the spring algorithm correctness was tested with synthetic models. Simulation verifications are presented.