• DocumentCode
    3565330
  • Title

    Innovative nearfield electromagnetic imaging system

  • Author

    Tabassum, Muhammad Naveed ; Elshafiey, Ibrahim ; Alam, Mubashir

  • Author_Institution
    Electr. Eng. Dept., King Saud Univ., Riyadh, Saudi Arabia
  • fYear
    2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    An innovative reconstruction system using compressed sensing for nearfield electromagnetic imaging is presented in this paper. The proposed imaging system is tested and validated by creating a dictionary for head imaging of single and multiple brain tumor targets. The scattered time-domain signals are collected at few sensor positions, considering a limited number of possible spatial locations of tumor targets, and using spatial compressed sensing. TPhe sensed signals are further preprocessed for spectral sparsity in frequency domain, resulting in further reduction in the number of samples. Simulation of the forward problem is presented, considering a head model, using CST Microwave Studio tool. Image reconstruction is performed considering various levels of signal to noise ratio. The quality of the reconstructed images of the target space reveals the potential of the developed imaging system.
  • Keywords
    brain; compressed sensing; electromagnetic wave scattering; image reconstruction; medical image processing; spectral analysis; time-frequency analysis; tumours; CST Microwave Studio tool; brain tumor targets; frequency domain anaysis; head imaging; head model; image reconstruction; nearfield electromagnetic imaging system; scattered time-domain signal; signal to noise ratio; spatial compressed sensing; spatial location; spectral sparsity; Arrays; Compressed sensing; Dictionaries; Head; Image reconstruction; Imaging; Tumors; Nearfield imaging; electromagnetic imaging; head imaging; spatial compressed sensing; spectral compressed sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Smart Instrumentation, Measurement and Applications (ICSIMA), 2014 IEEE International Conference on
  • Print_ISBN
    978-1-4799-8039-0
  • Type

    conf

  • DOI
    10.1109/ICSIMA.2014.7047428
  • Filename
    7047428