Virtual human bone modelling by interactive sculpting, mesh morphing and force-feedback

  • Marco Evangelos BiancoliniEmail author
  • Pier Paolo Valentini
Original Paper


The paper deals with an investigation on the role of interactive sculpting and radial basis function (RBF) mesh morphing in the field of biomechanical computer-aided simulations. In this context, mesh morphing can be effectively used in predictive medicine workflows where a patient-specific numerical model is taken as reference to understand the physics of interest by means of simulation-driven techniques. The proposed methodology is intended for addressing the interactive geometry modification in combination with a force-feedback device and it is applied to anatomical structures. The concept is demonstrated showing a fast remodelling workflow of the human femur. The interactive process allows to steer the morphing of a template FEA model onto the patient geometry by positioning a set of landmark points. A first morphing action allows to warp the solid model according to the RBF deformation field produced by landmarks, a final projection on the target surface is performed to complete the task. The approach proven to be quick, effective and ergonomic thanks to the haptic device and the high level of interactivity. New patient specific CAE models are generated in a very short time preserving the very good quality of the computational mesh.


Mesh morphing Radial basis functions Interactive modelling Force-feedback Biomechanics Virtual prototyping 



This work was partially supported by the University of Rome “Tor Vergata” within the “Uncovering Excellence” Programme. The input models used in the study have been kindly provided by Michael Kuron and Nicholas Veikos of CAE Associates, Inc (


  1. 1.
    Corney, J., Lim, T.: 3D modeling with ACIS. Saxe-Coburg Publication, Stirling (2001)Google Scholar
  2. 2.
    Bill, J.R., Lodha, S.K.: Sculpting polygonal models using virtual tools. In: CHCCS Graphics Interface, pp. 272–278 (1995)Google Scholar
  3. 3.
    Wong, J.P.Y., Lau, R.W.H., Ma, L.: Virtual 3D sculpting. J. Vis. Comput. Animat. 11, 155–66 (2000)CrossRefGoogle Scholar
  4. 4.
    Zheng, J.M., Chan, K.W., Gibson, I.: Constrained deformation of freeform surfaces using surface features for interactive design. Int. J. Adv. Manuf. Technol. 22(1–2), 54–67 (2003)CrossRefGoogle Scholar
  5. 5.
    Sederberg, T.W., Parry, S.R.: Free-form deformation of solid geometric models. In: Proceedings of ACM SIGGRAPH ’86, New York, NY, USA, pp. 151–160 (1986)Google Scholar
  6. 6.
    de Boer, A., van der Schoot, M.S., Bijl, H.: Mesh deformation based on radial basis function interpolation. Comput. Struct. 85(11–14), 784–795 (2007)CrossRefGoogle Scholar
  7. 7.
    Botsch, M., Kobbelt, L.: Real-time shape editing using radial basis functions. In: Proceedings of EUROGRAPHICS 2005 (2005)Google Scholar
  8. 8.
    Kojekine, N., Savchenko, V., Senin, M., Hagiwara, I.: A prototype system for character animation based on real-time deformations. J. Three Dimens. Images 16(4), 91–95 (2002)Google Scholar
  9. 9.
    Biancolini, M.E., Biancolini, C., Costa, E., Gattamelata, D., Valentini, P.P.: Industrial application of the meshless morpher RBF morph to a motorbike windshield optimisation. In: Proceedings of European automotive simulation conference (EASC), Munich, Germany (2009)Google Scholar
  10. 10.
    Biancolini, M.E.: Mesh morphing and smoothing by means of radial basis functions (RBF): a practical example using fluent and RBF morph. In: Leng, J., Sharrock, W. (eds.) Handbook of Research on Computational Science and Engineering: Theory and Practice, pp. 347–380. IGI Global, Hershey, PA (2012).
  11. 11.
    Sieger, D., Menzel, S., Botsch, M.: RBF morphing techniques for simulation-based design optimization. Eng. Comput. 30(2), 161–174 (2014)CrossRefGoogle Scholar
  12. 12.
    Cella, U., Biancolini, M.E.: Aeroelastic analysis of aircraft wind-tunnel model coupling structural and fluid dynamic codes. J. Aircr. 49, 407–414 (2012)CrossRefGoogle Scholar
  13. 13.
    Andrejašič, M., Eržen, D., Costa, E., Porziani, S., Biancolini, M.E., Groth, C.: A mesh morphing based FSI method used in aeronautical optimization applications. In: Proceedings of VII European Congress on Computational Methods in Applied Sciences and Engineering, Athens, Greece (2016)Google Scholar
  14. 14.
    Biancolini, M.E., Viola, I., Riotte, M.: Sails trim optimisation using CFD and RBF mesh morphing. Comput. Fluids 93, 46–60 (2014)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Khondge, A., Sovani, S.: An accurate, extensive, and rapid method for aerodynamics optimization: the 50:50:50 method. SAE Technical Paper 2012-01-0174 (2012)Google Scholar
  16. 16.
    Costa, E. Papoutsis-Kiachagias, E.M., Porziani, S., Biancolini, M.E., Giannakoglou, K.C., Groth, C.: Aerodynamic optimization of car shapes using the continuous adjoint method and an RBF morpher. In: Proceedings of EUROGEN2015 (2015)Google Scholar
  17. 17.
    Biancolini, M.E., Ponzini, R., Antiga, L., Morbiducci, U.: A new workflow for patient specific image-based hemodynamics: parametric study of the carotid bifurcation. In: Di Giamberardino, P., Iacoviello, D., Tavares, J., Natal Jorge, R. (eds.) Computational Modelling of Objects Represented in Images III. Fundamentals, Methods and Applications. CRC Press, London (2012)Google Scholar
  18. 18.
    Gallo, D., Biancolini, M.E., Ponzini, R., Antiga, L., Rizzo, G., Audenino, A., Morbiducci, U.: A virtual test bench for hemodynamic evaluation of aortic cannulation in cardiopulmonary bypass. In: 11th World Congress on Computational Mechanics. Barcelona, Spain, July 20–25 (2014)Google Scholar
  19. 19.
    Capellini, K., Costa, E., Biancolini, M.E., Vignali, E., Positano, V., Landini, L., Celi, S.: An image-based and RBF mesh morphing CFD simulation for parametric aTAA hemodynamics. In: Proceedings VII Meeting Italian Chapter of the European Society of Biomechanics (ESB-ITA 2017). Giuseppe Vairo, Editor (2017)Google Scholar
  20. 20.
    Lim, C.W., Su, Y., Yeo, S.Y., Ng, G.M., Nguyen, V.T., et al.: Automatic 4D reconstruction of patient-specific cardiac mesh with 1-to-1 vertex correspondence from segmented contours lines. PLoS ONE 9(4), e93747 (2014)CrossRefGoogle Scholar
  21. 21.
    Bonaretti, S., Seiler, C., Boichon, C., Reyes, M., Büchler, P.: Image-based vs. mesh-based statistical appearance models of the human femur: implications for finite element simulations. Med. Eng. Phys. 36(12), 1626–1635 (2014)CrossRefGoogle Scholar
  22. 22.
    Grassi, L., Schileo, E., Boichon, C., Viceconti, M., Taddei, F.: Comprehensive evaluation of PCA-based finite element modelling of the human femur. Med. Eng. Phys. 36(10), 1246–1252 (2014)CrossRefGoogle Scholar
  23. 23.
    Grassi, L., Hraiech, N., Schileo, E., Ansaloni, M., Rochette, M., Viceconti, M.: Evaluation of the generality and accuracy of a new mesh morphing procedure for the human femur. Med. Eng. Phys. 33(1), 112–120 (2011)CrossRefGoogle Scholar
  24. 24.
    Li, Z., Han, X., Ge, H., Ma, C.: A semi-automatic method of generating subject-specific pediatric head finite element models for impact dynamic responses to head injury. J. Mech. Behav. Biomed. Mater. 60, 557–567 (2016)CrossRefGoogle Scholar
  25. 25.
    Colombo, G., Rizzi, C., Regazzoni, D., Vitali, A.: 3D interactive environment for the design of medical devices. Int. J. Interact. Des. Manuf. 12(2), 699–715 (2018)CrossRefGoogle Scholar
  26. 26.
    Valentini, P.P., Biancolini, M.E.: Interactive sculpting using augmented-reality, mesh morphing, and force feedback: force-feedback capabilities in an augmented reality environment. IEEE Consum. Electron. Mag. 7(2), 83–90 (2018)CrossRefGoogle Scholar
  27. 27.
    Kim, L., Park, W., Cho, H., Park, S.: A universal remote control with haptic interface for customer electronic devices. IEEE Trans. Consum. Electron. 56(2), 913–918 (2010)CrossRefGoogle Scholar
  28. 28.
    Fischer, X., Coutellier, D.: The interaction: a new way of designing. In: Fischer, X., Coutellier, D. (eds.) Research in Interactive Design, pp. 1–15. Springer, Paris (2006)Google Scholar
  29. 29.
    Bhumann, M.D.: Radial Basis Functions: Theory and Implementations. Cambridge University Press, Cambridge (2003)CrossRefGoogle Scholar
  30. 30.
    Turk, G., O’Brien, J.F.: Modeling with implicit surfaces that interpolate. ACM Trans. Gr. 21(4), 855–73 (2002)CrossRefGoogle Scholar
  31. 31.
    Biancolini, M.E.: Fast Radial Basis Functions for Engineering Applications. Springer, Berlin (2018)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag France SAS, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Enterprise Engineering “Mario Lucertini”University of Rome “Tor Vergata”RomeItaly

Personalised recommendations