• DocumentCode
    471966
  • Title

    A Fast Linear Reconstruction Method for Scanning Impedance Imaging

  • Author

    Liu, Hongze ; Hawkins, Aaron R. ; Schultz, Stephen M. ; Oliphant, Travis E.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Brigham Young Univ., Provo, UT
  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 3 2006
  • Firstpage
    4277
  • Lastpage
    4280
  • Abstract
    Scanning electrical impedance imaging (SII) has been developed and implemented as a novel high resolution imaging modality with the potential of imaging the electrical properties of biological tissues. In this paper, a fast linear model is derived and applied to the impedance image reconstruction of scanning impedance imaging. With the help of both the deblurring concept and the reciprocity principle, this new approach leads to a calibrated approximation of the exact impedance distribution rather than a relative one from the original simplified linear method. Additionally, the method shows much less computational cost than the more straightforward nonlinear inverse method based on the forward model. The kernel function of this new approach is described and compared to the kernel of the simplified linear method. Two-dimensional impedance images of a flower petal and cancer cells are reconstructed using this method. The images reveal details not present in the measured images
  • Keywords
    cancer; electric impedance imaging; image restoration; medical image processing; tumours; biological tissues; cancer cell; electrical properties; flower petal; image deblurring; impedance image reconstruction; nonlinear inverse method; reciprocity principle; scanning electrical impedance imaging; Biological system modeling; Biological tissues; Cancer; Computational efficiency; High-resolution imaging; Image reconstruction; Impedance; Inverse problems; Kernel; Reconstruction algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
  • Conference_Location
    New York, NY
  • ISSN
    1557-170X
  • Print_ISBN
    1-4244-0032-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2006.260800
  • Filename
    4462746