• DocumentCode
    847898
  • Title

    Improved methods to determine optimal currents in electrical impedance tomography

  • Author

    Hua, Ping ; Woo, Eung Je ; Webster, John G. ; Tompkins, Willis J.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
  • Volume
    11
  • Issue
    4
  • fYear
    1992
  • fDate
    12/1/1992 12:00:00 AM
  • Firstpage
    488
  • Lastpage
    495
  • Abstract
    An electrical impedance tomography (EIT) system that uses the optimal current method to inject currents and the regularized Newton-Raphson algorithm to reconstruct an image of resistivity distribution is discussed. Iterative methods to derive the optimal current patterns through iterative physical measurements are developed. Direct methods to first determine the resistance matrix of a resistivity distribution through a set of current bases is injected and the measured voltage responses are stored. This permits iterative reconstruction techniques to operate on the stored data without requiring lengthy data taking from the object and reduces the effects of motion artifacts. The direct methods have superior performance as compared to the iterative methods in both optimal current and voltage generation. The results obtained with three sets of current bases are studied
  • Keywords
    electric impedance imaging; current injection; electrical impedance tomography; iterative physical measurements; measured voltage responses; medical diagnostic imaging; motion artifacts; optimal currents determination method; regularized Newton-Raphson algorithm; resistance matrix; resistivity distribution image reconstruction; Conductivity; Current measurement; Electric resistance; Electrical resistance measurement; Image reconstruction; Impedance; Iterative algorithms; Iterative methods; Tomography; Voltage;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/42.192684
  • Filename
    192684