• DocumentCode
    2112535
  • Title

    Inverse Radon Transform-Based Image Reconstruction using Various Frequency Domain Filters in Parallel Beam Transmission Tomography

  • Author

    Qureshi, Shahzad Ahmad ; Mirza, Sikander M. ; Arif, M.

  • Author_Institution
    Pakistan Inst. of Eng. & Appl. Sci., Islamabad
  • fYear
    2005
  • fDate
    27-27 Aug. 2005
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Inverse Radon transform based image reconstruction is of prime importance in various areas of science and engineering. Over the years, many techniques have emerged as possible alternative to exact analytical solution including back-projection (BP) and filtered back-projection (FBP). In FBP various filters are applied namely Ram-Lak (ramp), Shepp-Logan, Cosine, Hamming and Hanning filters. These techniques are applied to the head phantom and the lung phantom. Best results as reconstructed image are obtained by FBP technique using Hanning filter, which is in agreement with findings of other researchers. Additionally, FBP technique using Hamming filter has been found as effective as FBP Hanning filter technique in both cases.
  • Keywords
    Radon transforms; filtering theory; frequency-domain analysis; image reconstruction; tomography; Hanning filters; back-projection; frequency domain filters; inverse Radon transform-based image reconstruction; parallel beam transmission tomography; Acoustic imaging; Acoustic measurements; Computed tomography; Extraterrestrial measurements; Filters; Frequency domain analysis; Geophysical measurements; Image reconstruction; Optical imaging; X-ray imaging; Back-Projection; Filtered Back-Projection preparation; Inverse Radon Transform; Sinogram;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering Sciences and Technology, 2005. SCONEST 2005. Student Conference on
  • Conference_Location
    Karachi
  • Print_ISBN
    978-0-7803-9442-1
  • Electronic_ISBN
    978-0-7803-9442-1
  • Type

    conf

  • DOI
    10.1109/SCONEST.2005.4382887
  • Filename
    4382887