New open-source software for gamma-ray spectra analysis

Copyright © 2022 Elsevier Ltd. All rights reserved..

Many commercially available software packages have been created to analyze gamma-ray spectra, but their source code has generally not been shared, although some users may wish to add or modify certain functionality, which is impossible without access to the source code. This study therefore presents a new open-source software package for the analysis of gamma-ray spectra. The name of the software is GSA (Gamma-ray Spectra Analysis), the source code of which is freely available through the GitHub website (https://github.com/LAHCEN-EL-AMRI/Gamma-Spectra-Analysis). The main function of this initial version of the software is to locate peaks, calculate areas, and identify corresponding radionuclides. A future version will complement this by measuring the concentrations of radionuclide elements. The software was validated by comparing its analysis results with those generated by three other software programs, namely Genie 2000, Maestro, and FitzPeaks. All the formulas used are explained in this work, which could be useful for researchers or students looking to create their own software packages for analyzing gamma-ray spectra.

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:185

Enthalten in:

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine - 185(2022) vom: 30. Juli, Seite 110227

Sprache:

Englisch

Beteiligte Personen:

El Amri, Lahcen [VerfasserIn]
Chetaine, Abdelouahed [VerfasserIn]
Amsil, Hamid [VerfasserIn]
El Mokhtari, Brahim [VerfasserIn]
Bounouira, Hamid [VerfasserIn]
Didi, Abdessamad [VerfasserIn]
Benchrif, Abdelfettah [VerfasserIn]
Laraki, Khalid [VerfasserIn]
Marah, Hamid [VerfasserIn]

Links:

Volltext

Themen:

Journal Article
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Anmerkungen:

Date Revised 16.05.2022

published: Print-Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.1016/j.apradiso.2022.110227

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM340179996