An iterative method to estimate x-ray attenuation coefficients in computed tomography

Document Type : Conference Proceedings

Authors

1 Medical imaging Research Centre, Shiraz University of Medical Sciences, Shiraz 7193635899, Iran

2 Ongil, 79 D3, Sivaya Nagar, Reddiyur Alagapuram, Salem 636004, India

3 Department of Instrumentation and Applied Physics, Indian Institute of Science, Bangalore 560012. India

Abstract

Introduction: The basis of image formation in Computed Tomography (CT) lies in the x-ray linear attenuation coefficient of the scanned material. Compton scattering and photoelectric effect are the dominant interactions of the x-ray photons with the subject, in the range of diagnostic radiology. These two coefficients are important in tissue characterization by Dual-Energy CT (DECT), determination of electron density and dose calculation in treatment planning system. The aim of this paper is to calibrate the CT system, to calculate Compton scattering and photoelectric effect by an iterative method.
Materials and Methods: Chemical compounds with known effective atomic number and electron density were scanned at 80, 110, and 130kVp. HU values of these compounds were used to calculate Compton scattering and photoelectric effect by an iterative method. The calculated coefficients were used to estimate the HU values of liquid samples and solid rods made of polymers, to evaluate our findings
Results: The coefficients were found up to the fifth order of iteration and the coefficients were found to match the data with 95% confidence at 80, 110, and 130 kVp. The maximum deviation between the calculated and actual HU values were less than 3% for liquid and solid samples at these kVp values.
Conclusion: Calibration of CT system by known chemical samples, by using iterative method of data analysis may give very accurate idea about the x-ray attenuation coefficients of samples. Results of this study may be used in tissue characterization by DECT inversion, and to estimate electron density and dose distribution in treatment planning systems

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History

  • Receive Date: 21 May 2018
  • Revise Date: 11 May 2019
  • Accept Date: 06 July 2018

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