• DocumentCode
    3238146
  • Title

    Informational modeling of tissue-like materials using ultrasound

  • Author

    Hoerig, Cameron ; Ghaboussi, Jamshid ; Insana, Michael

  • Author_Institution
    Dept. of Bioeng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • fYear
    2015
  • fDate
    16-19 April 2015
  • Firstpage
    239
  • Lastpage
    242
  • Abstract
    The correlation between disease pathology and tissue stiffness can be exploited to detect and potentially diagnose abnormal tissue states. Elastography is an imaging modality that attempts to image tissue stiffness by measuring local displacements caused by an applied force and calculating a strain map. Some elasticity imaging techniques attempt to assign a material parameter, such as Young´s or shear modulus, to the imaged region in an effort to increase specificity. Unfortunately, the inversion techniques require many simplifying assumptions which lead to errors in the parameter estimates. One possible solution to increase accuracy in estimation is to first build an empirical model of the tissue using measured force-displacement data, thus eliminating the need for a priori assumptions. We propose the use of informational models for this purpose.
  • Keywords
    Young´s modulus; biomechanics; biomedical ultrasonics; diseases; displacement measurement; elasticity; physiological models; shear modulus; Young modulus; disease pathology; elasticity imaging techniques; elastography; force-displacement data measurement; inversion techniques; shear modulus; strain map calculation; tissue stiffness imaging; ultrasound; Artificial neural networks; Force measurement; Iron; Load modeling; Strain; Training; Young´s modulus; Elasticity Imaging; Machine Learning; Neural Networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on
  • Conference_Location
    New York, NY
  • Type

    conf

  • DOI
    10.1109/ISBI.2015.7163858
  • Filename
    7163858