Identification of physical properties of swine liver for surgical simulation using a dynamic deformation model

Xiaoshuai Chen, Masano Nakayama, Teppei Tsujita, Xin Jiang, Satoko Abiko, Koyu Abe, Atsushi Konno, Masaru Uchiyama

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    4 Citations (Scopus)

    Abstract

    In recent medical field, surgical simulators with the technique of virtual reality are expected to provide a new means to support the surgical front. We have developed a simulation for brain surgery using a dynamic deformation model. Most of physics models, including the dynamic deformation model, are required to identify the physical properties of target tissues. In this research, we identified physical properties of swine liver. Young's Modulus, Poisson's Ratio and damping coefficient is necessary for the simulation. There are previous researches about identification of Young's Modulus, but that about identification of Poisson's Ratio and damping coefficient are few. Therefore, in this research, we conduct tension experiments to measure Young's Modulus and Poisson's Ratio, and vibration experiments to measure damping coefficient.

    Original languageEnglish
    Title of host publication2011 IEEE/SICE International Symposium on System Integration, SII 2011
    Pages655-660
    Number of pages6
    DOIs
    Publication statusPublished - 2011 Dec 1
    Event2011 IEEE/SICE International Symposium on System Integration, SII 2011 - Kyoto, Japan
    Duration: 2011 Dec 202011 Dec 22

    Publication series

    Name2011 IEEE/SICE International Symposium on System Integration, SII 2011

    Other

    Other2011 IEEE/SICE International Symposium on System Integration, SII 2011
    CountryJapan
    CityKyoto
    Period11/12/2011/12/22

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Control and Systems Engineering

    Fingerprint Dive into the research topics of 'Identification of physical properties of swine liver for surgical simulation using a dynamic deformation model'. Together they form a unique fingerprint.

    Cite this