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A Method for Estimating Patient Specific Parameters for Simulation of Tissue Deformation by Finite Element Analysis

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Natural and Artificial Models in Computation and Biology (IWINAC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7930))

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Abstract

This paper proposes a method for estimating patient-specific material parameters used in the finite element analysis which simulates soft tissue deformation. The estimation of suitable material parameters for a patient is important for a navigation system for endoscopic surgery. At first, many data of soft tissue deformation are generated by changing the material parameters. Next, using Principle Component Analysis, each data with high dimensional is converted into the lower vector. The relationship between the material parameter and the deformation is found in the lower potential space.

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References

  1. Fung, Y.C.: Biomechanics: Mechanical Properties of Living Tissues, 2nd edn. Springer (1993)

    Google Scholar 

  2. Hong, J., Matsumoto, N., Ouchida, R., Komune, S., Hashizume, M.: Medical navigation system for otologic surgery based on hybrid registration and virtual intraoperative computed tomography. IEEE Transactions on Biomedical Engineering 56(2), 426–432 (2009)

    Article  Google Scholar 

  3. Hoshi, T., Kobayashi, Y., Miyashita, T., Fujie, M.: Quantitative palpation to identify the material parameters of tissues using reactive force measurement and finite element simulation. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2822–2828 (2010)

    Google Scholar 

  4. Kauer, M., Vuskovic, V., Dual, J., Székely, G., Bajka, M.: Inverse finite element characterization of soft tissues. Medical Image Analysis 6(3), 275–287 (2002)

    Article  Google Scholar 

  5. Konishi, K., Nakamoto, M., Kakeji, Y., Tanoue, K., Kawanaka, H., Yamaguchi, S., Ieiri, S., Sato, Y., Maehara, Y., Tamura, S., Hashizume, M.: A real-time navigation system for laparoscopic surgery based on three-dimensional ultrasound using magneto-optic hybrid tracking configuration. International Journal of Computer Assisted Radiology and Surgery 2(1), 1–10 (2007)

    Article  Google Scholar 

  6. Matsumoto, N., Hong, J., Hashizume, M., Komune, S.: A minimally invasive registration method using surface template-assisted marker positioning (stamp) for image-guided otologic surgery. Otolaryngology - Head and Neck Surger 140(1), 96–102 (2009)

    Article  Google Scholar 

  7. Moffitt, T.P., Baker, D., Kirkpatrick, S.J., Prahl, S.A.: Mechanical properties of coagulated albumin and failure mechanisms of liver repaired using an argon beam coagulator with albumin. J. Biomedical Materials Research (Applied Biomaterials) 63, 722–728 (2002)

    Article  Google Scholar 

  8. Morooka, K., Chen, X., Kurazume, R., Uchida, S., Hara, K., Iwashita, Y., Hashizume, M.: Real-time nonlinear FEM with neural network for simulating soft organ model deformation. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part II. LNCS, vol. 5242, pp. 742–749. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  9. Morooka, K., Taguchi, T., Chen, X., Kurazume, R., Hashizume, M., Hasegawa, T.: An efficient construction of real-time fem-based simulator for soft tissue deformation with large dataset. In: CARS 2012, p. 427 (2012)

    Google Scholar 

  10. Mousavi, S.R., Khalaji, I., Naini, A.S., Raahemifar, K., Samani, A.: Statistical finite element method for real-time tissue mechanics analysis. Computer Methods in Biomechanics and Biomedical Engineering 15(6), 595–608 (2012)

    Article  Google Scholar 

  11. Riken: Human organs property database for computer simulation (2008), http://cfd-duo.riken.jp/cbms-mp/index.htm

  12. Volonte, F., Pugin, F., Bucher, P., Sugimoto, M., Ratib, O., Morel, P.: Augmented reality and image overlay navigation with osirix in laparoscopic and robotic surgery: not only a matter of fashion. Journal of Hepato-Biliary-Pancreatic Sciences 18(4), 506–509 (2011)

    Article  Google Scholar 

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Morooka, K., Sonoki, S., Kurazume, R., Hasegawa, T. (2013). A Method for Estimating Patient Specific Parameters for Simulation of Tissue Deformation by Finite Element Analysis. In: Ferrández Vicente, J.M., Álvarez Sánchez, J.R., de la Paz López, F., Toledo Moreo, F.J. (eds) Natural and Artificial Models in Computation and Biology. IWINAC 2013. Lecture Notes in Computer Science, vol 7930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38637-4_12

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  • DOI: https://doi.org/10.1007/978-3-642-38637-4_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38636-7

  • Online ISBN: 978-3-642-38637-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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