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.
Similar content being viewed by others
References
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
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
ANSI/IEEE Standard 325 (1986) Test procedures for germanium gamma-ray detectors. Nucl Plasma Sci Soc. doi:10.1109/IEEESTD.1987.81600
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
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
Shepp LA, Vardi Y (1982) Maximum likelihood reconstruction for emission tomography. Med Imaging. doi:10.1109/TMI.1982.4307558
Meng LJ, Ramsden D (2000) An inter-comparison of three spectral-deconvolution algorithms for gamma-ray spectroscopy. Nucl Sci. doi:10.1109/23.872973
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
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
Pelowitz DB (2013) MCNP6 User’s Manual Version 1.0. LA-CP-13-00634, Los Alamos National Security, LLC
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
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
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
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
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
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
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
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
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
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
MATLAB—The Language of Technical Computing. http://www.mathworks.com/ Accessed 02 Apr 2015
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
Corresponding author
Rights and permissions
About this article
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
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10967-015-4637-9