The Visual Computer

, Volume 31, Issue 4, pp 485–495 | Cite as

Deformable mesh simulation for virtual laparoscopic cholecystectomy training

  • Youngjun Kim
  • Laehyun Kim
  • Deukhee Lee
  • Sangkyun Shin
  • Hyunchul Cho
  • Frédérick Roy
  • Sehyung ParkEmail author
Original Article


Virtual simulation of laparoscopic surgery is getting attention for training novice surgeons and medical residents for practice. Virtual surgical simulation has many advantages because it can provide users with a safe environment without animal or patient subjects. Although several solutions are available in the market, there are no reported studies with detailed technical descriptions of the virtual simulation of laparoscopic cholecystectomy (gallbladder removal surgery), one of the major surgeries performed using laparoscopic surgical procedures. Here, we present a realistic laparoscopic cholecystectomy training simulator. The system was developed by applying state-of-the-art computer graphical technologies using an open source library and proposing a new method of deformable mesh carving. The deformable mesh carving is a volume-based method using potential fields and hexahedral finite element method. In this paper, we describe the detailed techniques used to realize the laparoscopic cholecystectomy simulation. The experimental and user study results prove that the presented system simulates the cholecystectomy procedures in real time with high degree of realism and fidelity.


Medical simulation Mesh deformation  Mesh carving  Mesh sculpting Cholecystectomy 



This research was supported by the KIST Institutional Program (2E24520, 2E24551).

Supplementary material

Supplementary material 1 (wmv 9704 KB)

Supplementary material 2 (wmv 2963 KB)


  1. 1.
    Soper, N.J., Stockmann, P.T., Dunnegan, D.L., Ashley, S.W.: Laparoscopic cholecystectomy. The new gold standard? Arch. Surg. 127(8), 917–921 (1992)CrossRefGoogle Scholar
  2. 2.
    WebSurg. Available at (2013)
  3. 3.
    Schijven, M.P., Jakimowicz, J.J., Broeders, I.A.M.J., Tseng, L.N.L.: The Eindhoven laparoscopic cholecystectomy training course improving operating room performance using virtual reality training: results from the first E.A.E.S. accredited virtual reality trainings curriculum. Surg. Endo. 19(9), 1220–1226 (2005)Google Scholar
  4. 4.
    Gauger, P.G., et al.: Laparoscopic simulation training with proficiency targets improves practice and performance of novice surgeons. Am. J. Surg. 199, 72–80 (2010)CrossRefGoogle Scholar
  5. 5.
    Zhang, A., Hunerbein, M., Dai, Y., Schlag, P.M., Beller, S.: Construct validity testing of a laparoscopic surgery simulator (Lap Mentor). Surg. Endosc. 22, 1440–1444 (2008)CrossRefGoogle Scholar
  6. 6.
    Peterlik, I., Nouicer, M., Duriez, C., Cotin, S., Kheddar, A.: Constraint-based haptic rendering of multirate compliant mechanisms. IEEE Trans. Haptics 4(3), 175–187 (2011)CrossRefGoogle Scholar
  7. 7.
    Yiasemidou, M., Glassman, D., Vasas, P., Badiani, S., Patel, B.: Faster simulated laparoscopic cholecystectomy with haptic feedback technology. Open Access Surg. 4, 39–44 (2011)CrossRefGoogle Scholar
  8. 8.
    SOFA. Available at (2013)
  9. 9.
    Faure, F., Duriez, C., Delingette, H., Allard, J., Gilles, B., Marchesseau, S., Talbot, H., Courtecuisse, H., Bousquet, G., Peterlik, I., Cotin, S.: Sofa: a multi-model framework for interactive physical simulation. Soft Tissue Biomech. Model. Comput. Assist. Surg. 283–321 (2012)Google Scholar
  10. 10.
    Courtecuisse, H., Jung, H., Allard, J., Duriez, C., Lee, D.Y., Cotin, S.: GPU-based real-time soft tissue deformation with cutting and haptic feedback. Prog. Biophys. Mol. Biol. 103(2), 159–168 (2010) Google Scholar
  11. 11.
    Pemmod, E., Semesant, M., Relan, J., Delingette, H.: Interactive real time simulation of cardiac radio-frequency ablation. VCBM 91–98, 2010 (2010)Google Scholar
  12. 12.
    Nesme, M., Kry, P.G., Jeřábková, L., Faure, F.: Preserving topology and elasticity for embedded deformable models. ACM Trans. Graph. 28(3), 52 (2009)CrossRefGoogle Scholar
  13. 13.
    SEP, SimSurgery Co., Available at (2013)
  14. 14.
    LAP Mentor, Simbionix Co., Available at (2013)
  15. 15.
    LapVR, Immersion Co., Available at (2013)
  16. 16.
    Gallagher, A.G., et al.: Virtual reality simulation for the operating room proficiency-based training as a paradigm shift in surgical skills training. Ann. Surg. 241(2), 364–372 (2005)CrossRefGoogle Scholar
  17. 17.
    Rajesh, A., Jonnie, W., Indran, B., Parvinderpal, S., Thanos, A., Ara, D.: Proving the effectiveness of virtual reality simulation for training in laparoscopic surgery. Ann. Surg. 246(5), 771–779 (2007)CrossRefGoogle Scholar
  18. 18.
    Basdogan, C., Ho, C.H., Srinivasan, M.A.: Virtual environments for medical training: graphical and haptic simulation of laparoscopic common bile duct exploration. IEEE/ASME Trans. Mech. 6(3), 269–285 (2001)CrossRefGoogle Scholar
  19. 19.
    Park, J.S., Chung, M.S., Hwang, S.B., Shin, B.S., Park, H.S.: Visible Korean human: its techniques and applications. Clin. Anat. 19, 216–224 (2006)CrossRefGoogle Scholar
  20. 20.
    Georgii, J., Westermann, R.: Corotated finite elements made fast and stable. VRIPHYS 11–19 (2008)Google Scholar
  21. 21.
    Labelle, F., Shewchuk, J.R.: Isosurface stuffing: fast tetrahedral meshes with good dihedral angles. ACM Trans. Graph. 26(3), 1–10 (2007)CrossRefGoogle Scholar
  22. 22.
    Nesme, M., Marchal, M., Promayon, E., Chabanas, M., Payan, Y., Faure, F.: Physically realistic interactive simulation for biological soft tissues. Recent Res. Dev. Biomech. 2 (2005)Google Scholar
  23. 23.
    Hubert, N.: GPU Gems 3. Lab Companion Series 3. Addison-Wesley, ISBN 0321515269 (2008)Google Scholar
  24. 24.
    Bruyns, C.D., Montgomery, K.: Generalized interactions using virtual tools within the Spring framework: probing, piercing, cauterizing and ablating. Stud. Health Tech. Inform. 85, 74–78 (2002)Google Scholar
  25. 25.
    Kim, Y., Lee, S., Roy, F., Lee, D., Kim, L., Park, S.: Carving mesh with deformation for soft tissue removal simulation. In: Mesh Processing in Medical Image Analysis, pp. 70–79 (2012)Google Scholar
  26. 26.
    Kim, L.H., Park, S.H.: Haptic interaction and volume modeling techniques for realistic dental simulation. Visual Comput. 22, 90–98 (2006)CrossRefGoogle Scholar
  27. 27.
    Mauch, S.: A fast algorithm for computing the closest point and distance transform. Technical Report. Available at (2013)
  28. 28.
    Velho, L., Figureiredo, L.H.D., Gomes, J.: A unified approach for hierarchical adaptive tessellation of surfaces. ACM Trans. Graph. 18(4), 329–360 (1999)CrossRefGoogle Scholar
  29. 29.
    Jeřábková, L., Bousquet, G., Barbier, S., Faure, F., Allard, J.: Volumetric modeling and interactive cutting of deformable bodies. Prog. Biophys. Mol Biol. 103(2), 217–224 (2010)CrossRefGoogle Scholar
  30. 30.
    Kim, Y., Chang, D., Kim, J., Park, S.: Gallbladder removal simulation for laparoscopic surgery training: a hybrid modeling method. J. Comput. Sci. Technol. 28(3), 499–507 (2013)CrossRefGoogle Scholar
  31. 31.
    Duriez, C., Cotin, S., Lenoir, J., Neumann, P.: New approaches to catheter navigation for interventional radiology simulation. Comput. Aided Surg. 11(6), 300–308 (2006)Google Scholar
  32. 32.
    Rapidform XOR3, INUS Tech. Co., Available at (2013)
  33. 33.
    NT Research Co., Available at (2013)

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Youngjun Kim
    • 1
  • Laehyun Kim
    • 1
  • Deukhee Lee
    • 1
  • Sangkyun Shin
    • 1
  • Hyunchul Cho
    • 1
  • Frédérick Roy
    • 1
  • Sehyung Park
    • 1
    Email author
  1. 1.Korea Institute of Science and Technology (KIST)SeoulRepublic of Korea

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