Application of CT Simulation Technique for Virtual Ultra-Low-Dose Trial in CT Colonography

  • Chang Won Kim
  • Jong Hyo Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7601)


A low-dose CT simulation technique is presented which might allow for a virtual ultra-low-dose trial in CT colonography without requiring raw sinogram data. A virtual sinogram is generated by performing the line integral of the CT number-based attenuation value with use of the CT scan parameters available in the DICOM header and in the literature. A separate noise sinogram is generated with use of a noise model, which incorporates the X-ray photon flux depending on the mAs, system electronic noise, and virtual sinogram. A synthetic noise CT image is generated by application of the filtered back projection of the noise sinogram with use of an appropriate filter that depends on the reconstruction kernel of the original CT. Finally, a simulated low-dose CT image is generated by addition of the CT data for the synthetic noise to the original CT data. Clinical CT colonography images with and without fecal tagging were used as simulation input and 50%, 25%, and 12.5% dose images were generated and evaluated. Our results suggest that the proposed CT simulation technique has potential for application in virtual ultra-low-dose trial in CT colonography in which an unlimited number of scan protocols could be performed without repetition of the real CT exposure to the patients.


Algorithmic modulation transfer noise power spectrum low-dose simulation filtered back projection 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Chang Won Kim
    • 1
    • 4
  • Jong Hyo Kim
    • 1
    • 2
    • 3
    • 4
    • 5
  1. 1.Interdisciplinary Program of BioengineeringSeoul National University, College of EngineeringSeoulKorea
  2. 2.Department of RadiologySeoul National University College of MedicineKorea
  3. 3.Interdisciplinary Program in Radiation Applied Life ScienceSeoul National University College of MedicineKorea
  4. 4.Institute of Radiation MedicineSeoul National University Medical Research CenterSeoulKorea
  5. 5.Department of Intelligent Convergence Systems, Graduate School of Convergence Science and TechnologySeoul National UniversitySuwon-siKorea

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