Mesh Topology Identification for Mass-Spring Models

Abstract

Abstract. In surgical simulations, the two most popular approaches to model soft tissues are Finite Element Method (FEM) and Mass-Spring System (MSS). Main advantages of FEM are accuracy and realism. Furthermore, the model allows the direct integration of experimentally obtained biomechanical tissue parameters. However, computation times remain high, limiting real-time application of the method. In contrast to this, the main advantage of MSS is low computational complexity and simple implementation. These factors make the latter method highly attractive for virtual reality based surgical simulators. However, the specification of system parameters for a MSS (masses, spring constants, mesh topology) is not straightforward and remains a major difficulty of the approach. In this paper, we propose a solution to this problem based on evolutionary algorithms -our current focus being the determination of mesh topology. We use reference models to obtain the topology of a MSS. First results demonstrate, that the exact recovery of isotropic and anisotropic reference mesh configurations is possible.

Automatic preparation, calibration, and simulation of deformable objects

“…Bianchi et al [8] demonstrate that a calibration procedure can enable a 2D mass-spring system to recover the connectivity of another 2D mass-spring system; deformation constants are held constant. Bianchi et al [9] later demonstrate the recovery of spring constants, and the 2D calibration of a mass-spring system to a finite element reference model.…”

Simultaneous Topology and Stiffness Identification for Mass-Spring Models Based on FEM Reference Deformations

“…In [1] we proposed an approach based on genetic optimization to identify the topology of mass-spring systems. A MSM (the learning model ) was trained by means of a known model (the reference model ) undergoing stretching and shearing induced by external forces.…”

“…Parameters, such as mass distribution, coefficients of spring transfer functions and overall connectivity have to be determined. In [1], we have suggested an approach based on genetic optimization for the identification of MSM parameters. Our initial focus has been on mesh topology.…”

Force-Based Calibration of a Particle System for Realistic Simulation of Nonlinear and Viscoelastic Soft Tissue Behavior

“…In [2], the authors establish a link between discrete mass-spring models and the classical theory of elasticity. In [3], a genetic optimization algorithm is used to determine the topology of the mass-spring system. In [4], a 2D mass-springdamper system is trained to behave like a nonlinear FEM.…”