The Visual Computer

, Volume 31, Issue 6–8, pp 947–957 | Cite as

Metaballs-based physical modeling and deformation of organs for virtual surgery

  • Junjun Pan
  • Chengkai Zhao
  • Xin Zhao
  • Aimin Hao
  • Hong Qin
Original Article


Prior research on metaballs-based modeling solely focuses on shape geometry and its processing for organic objects. This paper takes a different approach by exploring a new metaballs-based physical modeling method for digital organs that are imperative to support virtual surgery. We propose a novel hybrid physical model comprising both surface mesh and the metaballs which occupy organs’ interior. The finer surface mesh with high-precision geometric information and texture is necessary to represent the boundary structure of organs. Through the use of metaballs, the organ interior is geometrically simplified via a set of overlapping spheres with different radii. This work’s novelty hinges upon the integration of metaballs and position-based dynamics (PBD) which enables metaballs-based organs to serve as physical models and participate in dynamic simulation. For the metaballs construction, we develop an adaptive approach based on Voronoi Diagram for model initialization. Using global optimization, an electrostatic attraction model is proposed to drive the metaballs to best match with the organ’s boundary. Using PBD, we devise a novel metaballs-based deformation algorithm, which preserves two local shape properties via constraints on Laplacian coordinates and local volume. To retain the organ’s smooth deformation, we propose a new skinning method based on distance field, and it is employed to build the mapping between the metaballs and organ boundary. This metaballs-based deformation technique has already been integrated into a VR-based laparoscopic surgery simulator.


Metaballs Optimization Organ  Deformation  Skinning 



We thank Junxuan Bai and Chen Yang for their work in the experiments. This research is supported by National Natural Science Foundation of China (No. 61402025, 61190120, 61190121, 61190125), National Science Foundation of USA (No. IIS-0949467, 1047715, 1049448) and the Fundamental Research Funds for the Central Universities


  1. 1.
  2. 2.
  3. 3.
    Wu, J., Dick, C., Westerman, R.: Physically-based simulation of cuts in deformable bodies: a survey. Eurographics 7(3), 1–19 (2014)Google Scholar
  4. 4.
    Muraki, S.: Volumetric shape description of range data using blobby model. Comput. Graph. 25(4), 227–235 (1991)CrossRefGoogle Scholar
  5. 5.
    Wei, Y., Cotin, S., Dequidt, J.: A (Near) real-time simulation method of aneurysm coil embolization. Aneurysm 8(29), 223–248 (2012)Google Scholar
  6. 6.
    Gianluca D.N., Melchiorri C.: Surgery simulations and haptic feedback: a new approach for local interaction using implicit surfaces. International Conference on Applied Bionics and Biomechanics, Venice, Oct. pp. 23–28 (2010)Google Scholar
  7. 7.
    Cueto, E., Chinesta, F.: Real time simulation for computational surgery: a review. Adv. Model. Simul. Eng. Sci. 1(11), 1–18 (2014)Google Scholar
  8. 8.
    Wu, J., Dick, C., Westermann, R.: Efficient collision detection for composite finite element simulation of cuts in deformable bodies. Vis. Comput. 29(6–8), 739–749 (2013)CrossRefGoogle Scholar
  9. 9.
    Jeřábková, L., Torsten, K.: Stable cutting of deformable objects in virtual environments using XFEM. IEEE Comput. Graph. Appl. 29(2), 61–71 (2009)CrossRefGoogle Scholar
  10. 10.
    Liu, T., Bargteil, A.W., O’Brien, J.F., Kavan, L.: Fast simulation of mass-spring systems. ACM Trans. Graph. 32(6), 1–7 (2013)Google Scholar
  11. 11.
    Pan, J., Chang, J., Yang, X., Qureshi, T., Howell, R., Hickish, T., Zhang, J.: Graphic and haptic simulation system for virtual laparoscopic rectum surgery. Int. J. Med. Robot. Comput. Assist. Surg. 7(3), 304–317 (2011)Google Scholar
  12. 12.
    Jones, B., Ward, S., Jallepalli, A., Perenia, J., Bargteil, A.W.: Deformation embedding for point-based elastoplastic simulation. ACM Trans. Graph. 33(2), 1–9 (2014)CrossRefGoogle Scholar
  13. 13.
    Steinemann, D., Miguel, A.O., Gross M.: Fast arbitrary splitting of deforming objects. In: Proceedings of the 2006 ACM SIGGRAPH/Eurographics symposium on Computer animation, Sep 10, 63–72, (2006)Google Scholar
  14. 14.
    Pietroni, N., Ganovelli, F., Cignoni, P., Scopigno, R.: Splitting cubes: a fast and robust technique for virtual cutting. Vis. Comput. 25(3), 227–289 (2009)CrossRefGoogle Scholar
  15. 15.
    Bender, J., Müller, M., Teschner, M., Macklin, M.: A survey on position based simulation methods in computer graphics. Comput. Graph. Forum 33(6), 228–251 (2014)CrossRefGoogle Scholar
  16. 16.
    Macklin, M., Müller, M., Chentanez, N., Kim, T.Y.: Unified particle physics for real-time applications. ACM Trans. Graph. 33(4), 1–10 (2014)CrossRefGoogle Scholar
  17. 17.
    France, L., Angelidis, A., Meseure, P., Cani, M.P., Lenoir, J., Faure, F., Chaillou, C.: Implicit Representations of the Human Intestines for Surgery Simulation. In: ESAIM: Proceedings, Nov. 12, pp. 42–47 (2002)Google Scholar
  18. 18.
    Suzuki, S., Suzuki, N., Hattori, A., Uchiyama, A., Kobayashi, S.: Sphere-filled organ model for virtual surgery system. IEEE Trans. Med. Imaging 23(6), 714–722 (2004)CrossRefGoogle Scholar
  19. 19.
    Bradshaw, G., Sullivan, C.O.: Sphere-tree construction using dynamic medial axis approximation. In: Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation, pp. 33–40 (2002)Google Scholar
  20. 20.
    Bradshaw, G., Sullivan, C.O.: Adaptive medial-axis approximation for sphere-tree construction. ACM Trans. Graph. 23(1), 1–26 (2004)CrossRefGoogle Scholar
  21. 21.
    Hubbard, P.M.: Approximating polyhedra with spheres for time-critical collision detection. ACM Trans. Graph. 15(3), 179–210 (1996)CrossRefGoogle Scholar
  22. 22.
  23. 23.
    Sorkine-Hornung, O., Cohen-Or, D., Lipman, Y., Alexa, M., Roessl, C., Seidel, H.-P.: Laplacian Surface Editing. Eurographics Symposium on Geometry Processing, pp. 1–10 (2004)Google Scholar
  24. 24.
    Pan, J., Yang, X., Xie, X., Willis, P., Zhang, J.: Automatic rigging for animation characters with 3D silhouette. Comput. Anim. Virtual Worlds 20(2–3), 121–131 (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Junjun Pan
    • 1
  • Chengkai Zhao
    • 1
  • Xin Zhao
    • 1
  • Aimin Hao
    • 1
  • Hong Qin
    • 2
  1. 1.State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijingChina
  2. 2.Department of Computer ScienceStony Brook University (SUNY Stony Brook)New YorkUSA

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