Skip to main content
Log in

Application of the ML-EM algorithm in the suppression of Compton background of gamma-ray spectroscopy system

  • Published:
Journal of Radioanalytical and Nuclear Chemistry Aims and scope Submit manuscript

Abstract

In the present study, the Compton background of the measured gamma-ray spectrum was suppressed by using the deconvolution method with applying the maximum likelihood fitting by expectation maximization (ML-EM) algorithm. The MATLAB program for deconvolution of the measured spectrum were written based on the applying of ML-EM algorithm in conjunction with a matrix of detector response functions within the energy range 0–1.9 MeV. The Compton Suppression Factor (SF) ratio of the deconvolved spectrum is increased by approximately 3–9 times relative to the measured spectrum of 137Cs and 60Cs, respectively. Additionally, the photopeak areas of deconvolved spectra were considerably raised to compare with ones of measured spectra owing to accumulating the counting numbers of the background into appropriate photopeaks.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Beach SM, DeWerd LA (2007) Deconvolution and reconstruction techniques of closely spaced low-energy spectra from high-purity germanium spectrometry. Nucl Instrum Methods A. doi:10.1016/j.nima.2006.12.006

    Google Scholar 

  2. Engdahl JC, Bharwani K (2005) Semi-analytical response function for ML-EM deconvolution of NaI detector energy spectra. Nucl Sci Symp Cone Rec. doi:10.1109/NSSMIC.2005.1596569

    Google Scholar 

  3. ANSI/IEEE Standard 325 (1986) Test procedures for germanium gamma-ray detectors. Nucl Plasma Sci Soc. doi:10.1109/IEEESTD.1987.81600

  4. Kiang LL, Tsou RH, Lin WJ (1993) A study on T-shape Compton suppression spectrometer by Monte Carlo simulation. Nucl Instrum Methods A. doi:10.1016/0168-9002(93)90708-P

    Google Scholar 

  5. Badrana HM, Sharsharb T (1999) An experimental method for the optimization of anti-Compton spectrometer. Nucl Instrum Methods A. doi:10.1016/S0168-9002(99)00573-2

    Google Scholar 

  6. Shepp LA, Vardi Y (1982) Maximum likelihood reconstruction for emission tomography. Med Imaging. doi:10.1109/TMI.1982.4307558

    Google Scholar 

  7. Meng LJ, Ramsden D (2000) An inter-comparison of three spectral-deconvolution algorithms for gamma-ray spectroscopy. Nucl Sci. doi:10.1109/23.872973

    Google Scholar 

  8. Gutiérrez-Villanueva JL, Martín-Martín A, Peña V, Iniguez MP, de Celis B (2008) Calibration of a portable HPGe detector using MCNP code for the determination of 137Cs in soils. J Environ Radioact. doi:10.1016/j.jenvrad.2007.12.016

    Google Scholar 

  9. Chham E, García FP, El Bardouni T, Ferro-García MA, Azahra M, Benaalilou K, Krikiz M, Elyaakoubi H, El Bakkali J, Kaddour M (2015) Monte Carlo analysis of the influence of germanium dead layer thickness on the HPGe gamma detector experimental efficiency measured by use of extended sources. Appl Radiat Isot. doi:10.1016/j.apradiso.2014.09.007

    Google Scholar 

  10. Pelowitz DB (2013) MCNP6 User’s Manual Version 1.0. LA-CP-13-00634, Los Alamos National Security, LLC

  11. Goorley T, James M, Booth T, Brown F, Bull J, Cox LJ, Durkee J, Elson J, Fensin M, Forster RA, Hendricks J, Hughes HG, Johns R, Kiedrowski B, Martz R, Mashnik S, McKinney G, Pelowitz D, Prael R, Sweezy J, Waters L, Wilcox T, Zukaitis T (2014) Features of MCNP6. Joint International Conference on Supercomputing in Nuclear Applications and Monte Carlo doi: 10.1051/snamc/201406011

  12. Challan MB (2013) Gamma-ray efficiency of a HPGe detector as a function of energy and geometry. Appl Radiat Isot. doi:10.1016/j.apradiso.2013.07.010

    Google Scholar 

  13. Ewa IOB, Bodizs D, Czifrus Sz, Molnar Zs (2001) Monte Carlo determination of full energy peak efficiency for a HPGe detector. Appl Radiat Isot. doi:10.1016/S0969-8043(00)00366-3

    Google Scholar 

  14. Boson J, Ågren G, Johansson L (2008) A detailed investigation of HPGe detector response for improved Monte Carlo efficiency calculations. Nucl Instrum Methods A. doi:10.1016/j.nima.2008.01.062

    Google Scholar 

  15. Dryak P, Kovar P (2006) Experimental and MC determination of HPGe detector efficiency in the 40–2754 keV energy range for measuring point source geometry with the source-to-detector distance of 25 cm. Appl Radiat Isot. doi:10.1016/j.apradiso.2006.02.083

    Google Scholar 

  16. Wu Y, Team FDS (2009) CAD-based interface programs for fusion neutron transport simulation. Fusion Eng Des. doi:10.1016/j.fusengdes.2008.12.041

    Google Scholar 

  17. Wu Y, Song J, Zheng H et al (2014) CAD-Based Monte Carlo program for integrated simulation of nuclear system SuperMC. Ann Fusion Energy. doi:10.1016/j.anucene.2014.08.058

    Google Scholar 

  18. Park CS, Choi HD, Sun GM, Whang JH (2008) Status of developing HPGe γ-ray spectrum analysis code HYPERGAM. Prog Nucl Energy. doi:10.1016/j.pnucene.2007.11.022

    Google Scholar 

  19. Park BG, Choi HD, Park CS (2012) New Development of Hypergam and its test of performance for γ-ray spectrum analysis. Nucl Eng Technol. doi:10.5516/NET.08.2011.062

    Google Scholar 

  20. Jandel M, Morháč M, Kliman J, Krupa L’, Matoušek V, Hamilton JH, Ramayy AY (2004) Decomposition of continuum γ-ray spectra using synthesized response matrix. Nucl Instrum Methods A. doi:10.1016/j.nima.2003.07.047

    Google Scholar 

  21. MATLAB—The Language of Technical Computing. http://www.mathworks.com/ Accessed 02 Apr 2015

Download references

Acknowledgments

This work was support by the National Research Foundation of KOREA (NFR). Grant funded by the KOREA goverment (MISP) (NRF-2012M2A2A6004263 & 2014M2A8A1048615).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gwang Min Sun.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hoang, S.M.T., Sun, G.M., Baek, H. et al. Application of the ML-EM algorithm in the suppression of Compton background of gamma-ray spectroscopy system. J Radioanal Nucl Chem 307, 2137–2146 (2016). https://doi.org/10.1007/s10967-015-4637-9

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10967-015-4637-9

Keywords

Navigation