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Stiffness parameter evaluation for graphical and haptic gallbladder model

Published: 26 November 2016 Publication History
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  • Abstract

    Surgery simulation platform is a combination of three components; deformable model; input output method and; collision detection method. Throughout the literature there are number of techniques, algorithms and mechanisms have been proposed to enhance the performances of those modules. In this paper we presents an extensive literature review on deformable object modeling algorithms, collision detection methods, haptic devices, haptic force feedback and rendering mechanism.
    Stiffness value is the governing parameter which decides the overall performance as well as the realism of the deformable models. With the stiffness it can increase or decrease the flexibility of the model. With the haptic force feedback it can sense the flexibility of the model. Hence it is important to impose an acceptable stiffness on model to enhance the user realism. Based on the methods which have been used to implement the deformable model, the acceptable stiffness value range may vary. In this paper it has discussed the stiffness parameter extraction process for the designed deformable gallbladder model under certain constraints and also has proposed an acceptable stiffness value range. The process has been evaluated based on the young modulus value of the live gallbladder tissue.

    References

    [1]
    Chinzei, K., & Miller, K. (1997). Compression of Swine Brain Tissue. Proc. XVIth ISB Congress, Tokyo, 1996--1997.
    [2]
    Keeve, E., Girod, S., Kikinis, R., & Girod, B. (1998). Deformable modeling of facial tissue for craniofacial surgery simulation. Computer Aided Surgery, 3(5), 228--238.
    [3]
    Delingette, H. (1998). Towards Realistic Soft Tissue Modeling in Medical Simulation. Proceedings of the IEEE, 86(3), 512--523.
    [4]
    Goethals, P. (2008). Tactile Feedback for Robot Assisted Minimally Invasive Surgery: an Overview.
    [5]
    Bro-Nielsen, M. (1997). Medical Image Registration and Surgery Simulation.
    [6]
    Terzopoulos, D., & Fleischer, K. (1988). Modeling inelastic deformation: viscolelasticity, plasticity, fracture. ACM Siggraph Computer Graphics, 22(4), 269--278.
    [7]
    W. Annicchiarico, G. Martinez, and M. Cerrolaza, "Boundary elements and B-spline surface modeling for medical applications," Applied Mathematical Modelling, pp. 194--208, 2007.
    [8]
    Gabor Szekély et al., "Virtual reality-based simulation of endoscopic surgery," Presence: Teleoperators and Virtual Environments, vol. 9, no. 3, pp. 310--333, 2000.
    [9]
    Nisansala, A., Weerasinghe, M., Dias, G., Sandaruwan, D., & Kodikara, N. (2015). Soft Tissue Modeling Techniques in Surgery Simulation. International Journal of Computer and Information Technology (IJCIT), 4(5), 826--831.
    [10]
    Granados, A. (2008). Haptic Deformable Shapes Using Open Source Libraries.
    [11]
    Mclaughlin, M. L. (2005). Touch in virtual environments: haptics and the design of interactive systems.
    [12]
    Kenneth Salisbury and Lin Mng, "Haptic Rendering - Beyond Visual Computing," IEEE Computer Graphics and Applications, pp. 22--23, 2004.
    [13]
    Teschner, M., Kimmerle, S., Heidelberger, B., Zachmann, G., Raghupathi, L., Fuhrmann, A., et al. (2005). Collision Detection for Deformable Objects. The Eurographics Association and Blackwell Publishing, 1--21.
    [14]
    Salisbury, K, Conti, F., & Barbagli, F. (n.d.). Haptic rendering: introductory concepts. Computer Graphics and Applications, IEEE, 24(2), 24--32.
    [15]
    Alessandro, F. (2005). A Multi-resolution Nonlinear Finite Element Approach to Real-time Simulation of Soft Tissue Deformation with Haptic Feedback.
    [16]
    Udwadia, F., & Farahani, A. (2008). Accelerated Runge-Kutta Methods. Discrete Dynamics in Nature and Society, 1--38.
    [17]
    Zingg, D., & Chisholm, T. (1999, 227--238). Runge-Kutta methods for linear ordinary differential equations. Applied Numerical Mathematics, 31(2).
    [18]
    Hervé Delingette and Nicholas Ayache, "Soft Tissue Modeling for Surgery Simulation," Computational models for the human body, pp. 453--550, 2004.
    [19]
    Ziv Soferman, David Blythe, and Nigel W. John, "Advanced graphics behind medical virtual reality: evolution of algorithms, hardware, and software interfaces," Proceedings of the IEEE, vol. 86, no. 3, pp. 531--554, 1998.
    [20]
    Esteban, G., Fernandez, C., Matellan, V., & Gonzalo, J. M. (2011, November). Computer surgery 3D simulations for a new teaching-learning model. In Serious Games and Applications for Health (SeGAH), 2011 IEEE 1st International Conference on (pp. 1--4). IEEE.
    [21]
    Liu, J., Zheng, Huaiyuan, Poh, Patrina, Machens, Hans-Günther, & Schilling, Arndt. (2015, July 14). Hydrogels for Engineering of Perfusable Vascular Networks. International Journal of Molecular Sciences, 16(7), 15997--16016.

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    cover image ACM Other conferences
    ICCIP '16: Proceedings of the 2nd International Conference on Communication and Information Processing
    November 2016
    272 pages
    ISBN:9781450348195
    DOI:10.1145/3018009
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 26 November 2016

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    Author Tags

    1. deformable model
    2. haptic rendering
    3. stiffness
    4. young modulus

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