• DocumentCode
    155397
  • Title

    Incorporating estimated Green´s functions in microwave breast cancer imaging with DORT

  • Author

    Abedin, Mohammed Jainul ; Hay, Stuart G. ; Collings, Iain B.

  • Author_Institution
    Comput. Inf., CSIRO, Marsfield, NSW, Australia
  • fYear
    2014
  • fDate
    4-6 March 2014
  • Firstpage
    163
  • Lastpage
    166
  • Abstract
    The decomposition of reversed time (DORT) method is a promising algorithm for microwave breast cancer imaging. However when DORT is applied to breasts with high percentage of glandular tissues, its performance decreases due to differences in the dielectric properties of the physical and computational media. We propose a new method of deriving pair wise permittivities by using the received scattered signals in a multi antenna imaging system. We propose to use the estimated permittivities when computing the Green´s function in the backpropagation step of DORT rather than using a nominal global value. We also propose to combine multiple eigenvectors of the time reversal operator. It is observed through simulation that our enhanced DORT method achieves improved focusing accuracy in detecting the breast malignancy.
  • Keywords
    Green´s function methods; biological tissues; biomedical imaging; cancer; dielectric properties; DORT; backpropagation step; decomposition of reversed time method; dielectric properties; estimated Green functions; glandular tissues; microwave breast cancer imaging; multi antenna imaging system; pair wise permittivities; received scattered signals; time reversal operator; Eigenvalues and eigenfunctions; Green´s function methods; Microwave imaging; Microwave theory and techniques; Permittivity; Tumors; DORT; Green´s function estimation; breast cancer detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Antenna Technology: "Small Antennas, Novel EM Structures and Materials, and Applications" (iWAT), 2014 International Workshop on
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    978-1-4799-2331-1
  • Type

    conf

  • DOI
    10.1109/IWAT.2014.6958627
  • Filename
    6958627