Abstract
Mass-spring systems are of special interest for soft tissue modeling in surgical simulation due to their ease of implementation and real-time behavior. However, the parameter identification (masses, spring constants, mesh topology) still remains a challenge. In previous work, we proposed an approach based on the training of mass-spring systems according to known reference models. Our initial focus was the determination of mesh topology in 2D. In this paper, we extend the method to 3D. Furthermore, we introduce a new approach to simultaneously identify mesh topology and spring stiffness values. Linear elastic FEM deformation computations are used as reference. Additionally, our results show that uniform distributions of spring stiffness constants fails to simulate linear elastic deformations.
Chapter PDF
Similar content being viewed by others
References
Bianchi, G., Harders, M., Székely, G.: Mesh topology identification for massspring models. In: MICCAI 2003, vol. 1, pp. 50–58 (2003)
Deussen, O., Kobbelt, L., Tucke, P.: Using simulated annealing to obtain good nodal approximations of deformable objects. Computer Animation and Simulation 1995, pp. 30–43 (1995)
Van Gelder, A.: Approximate simulation of elastic membr anes by triangulated spring meshes. Journal of Graphics Tools 3(2), 21–42 (1998)
Joukhadar, A., Garat, F., Laugier, C.: Parameter Identification for Dynamic Simulation. In: Proc. of the IEEE Int. Conf. on Robotics and Automation, Albuquerque, US, pp. 1928–1933 (1997)
Kauer, M., Vuskovic, V., Dual, J., Szekely, G., Bajka, M.: Inverse finite element characterization of soft tissues. Medical Image Analysis 6(3), 275–287 (2002)
Louchet, J., Provot, X., Crochemore, D.: Evolutionary identification of cloth animation models. Computer Animation and Simulation 1995, 44–54 (1995)
Maciel, A., Boulic, R., Thalmann, D.: Deformable tissue parameterized by properties of real biological tissue. In: IS4TM, pp. 74–87
Michlewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. Springer, Heidelberg (1999)
Nürnberger, A., Radetzky, A., Kruse, R.: A Problem Specific Recurrent Neural Network for the Description and Simulation of Dynamic Springs Models. In: IEEE IJCNN 1998, pp. 468–473 (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bianchi, G., Solenthaler, B., Székely, G., Harders, M. (2004). Simultaneous Topology and Stiffness Identification for Mass-Spring Models Based on FEM Reference Deformations. In: Barillot, C., Haynor, D.R., Hellier, P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30136-3_37
Download citation
DOI: https://doi.org/10.1007/978-3-540-30136-3_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22977-3
Online ISBN: 978-3-540-30136-3
eBook Packages: Springer Book Archive