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

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 base...

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Veröffentlicht in:Journal of radioanalytical and nuclear chemistry Jg. 307; H. 3; S. 2137 - 2146
Hauptverfasser: Hoang, Sy Minh Tuan, Sun, Gwang Min, Baek, Hani, Kim, Jiseok
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Dordrecht Springer Netherlands 01.03.2016
Springer
Schlagworte:
Algorithms
Chemistry
Chemistry and Materials Science
Detectors
Diagnostic Radiology
Gamma rays
Hadrons
Heavy Ions
Inorganic Chemistry
Nuclear Chemistry
Nuclear Physics
Physical Chemistry
Deconvolution
ML-EM
Compton suppression
Gamma spectroscopy
NAA
ISSN:0236-5731, 1588-2780
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Zusammenfassung: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 137 Cs and 60 Cs, 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.
ISSN:0236-5731
1588-2780
DOI:10.1007/s10967-015-4637-9