A Novel Modeling Framework for Multilayered Soft Tissue Deformation in Virtual Orthopedic Surgery

  • 672 Accesses

  • 19 Citations


Realistic modeling of soft tissue deformation is crucial to virtual orthopedic surgery, especially orthopedic trauma surgery which involves layered heterogeneous soft tissues. In this paper, a novel modeling framework for multilayered soft tissue deformation is proposed in order to facilitate the development of orthopedic surgery simulators. We construct our deformable model according to the layered structure of real human organs, and this results in a multilayered model. The division of layers is based on the segmented Chinese Visible Human (CVH) dataset. This enhances the realism and accuracy in the simulation. For the sake of efficiency, we employ 3D mass-spring system to our multilayered model. The nonlinear passive biomechanical properties of skin and skeletal muscle are achieved by introducing a bilinear elasticity scheme to the springs in the mass-spring system. To efficiently and accurately reproduce the biomechanical properties of certain human tissues, an optimization approach is employed in configuring the parameters of the springs. Experimental data from biomechanics literatures are used as benchmarking references. With the employment of Physics Processing Unit (PPU) and high quality volume visualization, our framework is developed into an interactive and intuitive platform for virtual surgery training systems. Several experiments demonstrate the feasibility of the proposed framework in providing interactive and realistic deformation for orthopedic surgery simulation.

This is a preview of subscription content, log in to check access.

Access options

Buy single article

Instant unlimited access to the full article PDF.

US$ 39.95

Price includes VAT for USA

Subscribe to journal

Immediate online access to all issues from 2019. Subscription will auto renew annually.

US$ 199

This is the net price. Taxes to be calculated in checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14


  1. 1.

    Nealen, A., Muller, M., Keiser, R., Boxerman, E., & Carlson, M. (2005). Physically based deformable models in computer graphics. In: Eurographics state of the art report.

  2. 2.

    Olga, S., Alexei, S., & Sen, H. (2007). Orthopaedic surgery training simulation. Journal of Mechanics in Medicine and Biology, 7(1), 37–53. World Scientific.

  3. 3.

    Bruce, D., Nordquist, P., Skarman, E., Mark, T., Gina, B., & David, B. (2006). Integrated lower extremity trauma simulator. In: Proceedings of medicine meets virtual reality 2006 (pp. 19–24). IOS Press.

  4. 4.

    Heng, P., Cheng, C., Wong, T., Wu, W., Xu, Y., Xie, Y., et al. (2006). Virtual reality techniques: Application to anatomic visualization and orthopaedics training. Clinical Orthopaedics and Related Research, 442, 5–12.

  5. 5.

    McCarthy, A., Moody, L., Waterworth, A., & Bickerstaff, D. (2006). Passive haptics in a knee arthroscopy simulator: Is it valid for core skills training? Clinical Orthopaedics and Related Research, 442, 13–20.

  6. 6.

    Reinig, K., Lee, C., Rubinstein, D., Bagur, M., & Spitzer, V. (2006). The united states military’s thigh trauma simulator. Clinical Orthopaedics and Related Research, 442, 45–56.

  7. 7.

    Joachim, G., & Rüdiger, W. (2005). Mass-spring systems on the gpu. Simulation Modelling Practice and Theory, 13, 693–702.

  8. 8.

    Mosegaard, J., & Sorensen, T. (2005). Gpu accelerated surgical simulators for complex morphology. In: Proceedings of the 2005 IEEE conference on virtual reality (pp. 147–153). Washington, DC: IEEE Computer Society.

  9. 9.

    Rasmusson, A., Mosegaard, J., & Sørensen, T. S. (2008). Exploring parallel algorithms for volumetric mass-spring-damper models in cuda. In: International symposium on computational models for biomedical simulation (pp. 49–58).

  10. 10.

    Spitzer, V., Ackerman, M., Scherzinger, A., & Whitlock, D. (1996). The visible human male: A technical report. Journal of the American Medical Informatics Assocication, 3(2), 118–130.

  11. 11.

    Park, J., Chung, M., Hwang, S., Lee, Y., Har, D., & Park, H. (2005). Visible Korean human: Improved serially sectioned images of the entire body. IEEE Transactions on Medical Imaging, 24(3), 352–260.

  12. 12.

    Zhang, S., Heng, P., Liu, Z., Tan, L., Qiu, M., et al. (2003). Creation of the chinese visible human data set. Anatomical Record (Part B: New Anatomy), 275, 190–195.

  13. 13.

    Heng, P., Zhang, S., Xie, Y., Wong, T., Chui, Y., & Cheng, C. (2006). Photorealistic virtual anatomy based on chinese visible human data. Clinical Anatomy, 19(3), 232–239.

  14. 14.

    Székely, G., Brechbuehler, C., Hutter, R., Rhomberg, A., & Schmid, P. (1998) Modeling of soft tissue deformation for laparoscopic surgery simulation. In: MICCAI ’98: Proceedings of the first international conference on medical image computing and computer-assisted intervention (pp. 550–561).

  15. 15.

    Wang, X., & Devarajan, V. (2004). A honeycomb model for soft tissue deformation. In: VRCAI ’04: Proceedings of the 2004 ACM SIGGRAPH international conference on virtual reality continuum and its applications in industry (pp. 257–260).

  16. 16.

    Fung, Y. (1993). Biomechanics: Mechanical properties of living tissues, (2nd ed.). Berlin: Springer.

  17. 17.

    Maurel, W., Wu, Y., Thalmann, N., & Thalmann, D. (1998). Biomechanical models for soft tissue simulation. Berlin: Springer.

  18. 18.

    Press, W., Teukolsky, S., Vettering, W., & Flannery, B. (2002). Numerical recipes in c++. The art of scientific computing. Cambridge: Cambridge University Press.

Download references


This work was supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region (Project No. CUHK 4461/05M). This work is affiliated with the Virtual Reality, Visualization and Imaging Research Center at The Chinese University of Hong Kong as well as the CUHK MoE-Microsoft Key Laboratory of Human-Centric Computing and Interface Technologies.

Author information

Correspondence to Jing Qin.

Electronic Supplementary Material

Below is the linked to the Electronic supplementary material.

(MOV 466 kb)

(MOV 556 kb)


(MOV 466 kb)


(MOV 556 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Qin, J., Pang, W., Chui, Y. et al. A Novel Modeling Framework for Multilayered Soft Tissue Deformation in Virtual Orthopedic Surgery. J Med Syst 34, 261–271 (2010).

Download citation


  • Multilayered deformable model
  • Bilinear modeling
  • Virtual orthopedic surgery