Neutron-gamma pulse shape discrimination for organic scintillation detector using 2D CNN based image classification

IF 1.6 3区工程技术 Q3 CHEMISTRY, INORGANIC & NUCLEAR

Applied Radiation and Isotopes Pub Date : 2025-01-21 DOI:10.1016/j.apradiso.2024.111653

Annesha Karmakar , Anikesh Pal , G. Anil Kumar , Bhavika , Vivek , Mohit Tyagi

{"title":"Neutron-gamma pulse shape discrimination for organic scintillation detector using 2D CNN based image classification","authors":"Annesha Karmakar , Anikesh Pal , G. Anil Kumar , Bhavika , Vivek , Mohit Tyagi","doi":"10.1016/j.apradiso.2024.111653","DOIUrl":null,"url":null,"abstract":"<div><div>This study shows an implementation of neutron-gamma pulse shape discrimination (PSD) using a two-dimensional convolutional neural network. The inputs to the network are snapshots of the unprocessed, digitized signals from a BC501A detector. By exposing a BC501A detector to a Cf-252 source, neutron and gamma signals were collected to create a training dataset. The realistic datasets were created using a data-driven approach for labeling the digitized signals, having classified snapshots of neutron and gamma pulses. Our algorithm was able to successfully differentiate neutrons and gammas with similar accuracy as the Charge Integration (CI) approach. Additionally, the independent dataset accuracy for our suggested 2D CNN-based PSD approach is 99%. In contrast to the traditional charge integration method, our suggested algorithm with data augmentation, is capable of extracting features from snapshots of the raw data based on the signal structures, making it computationally more efficient and also appropriate for other types of neutron detectors.</div></div>","PeriodicalId":8096,"journal":{"name":"Applied Radiation and Isotopes","volume":"217 ","pages":"Article 111653"},"PeriodicalIF":1.6000,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Radiation and Isotopes","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0969804324004810","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, INORGANIC & NUCLEAR","Score":null,"Total":0}

引用次数: 0

Abstract

This study shows an implementation of neutron-gamma pulse shape discrimination (PSD) using a two-dimensional convolutional neural network. The inputs to the network are snapshots of the unprocessed, digitized signals from a BC501A detector. By exposing a BC501A detector to a Cf-252 source, neutron and gamma signals were collected to create a training dataset. The realistic datasets were created using a data-driven approach for labeling the digitized signals, having classified snapshots of neutron and gamma pulses. Our algorithm was able to successfully differentiate neutrons and gammas with similar accuracy as the Charge Integration (CI) approach. Additionally, the independent dataset accuracy for our suggested 2D CNN-based PSD approach is 99%. In contrast to the traditional charge integration method, our suggested algorithm with data augmentation, is capable of extracting features from snapshots of the raw data based on the signal structures, making it computationally more efficient and also appropriate for other types of neutron detectors.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Applied Radiation and Isotopes 工程技术-核科学技术

CiteScore

3.00

自引率

12.50%

发文量

406

审稿时长

13.5 months

期刊介绍： Applied Radiation and Isotopes provides a high quality medium for the publication of substantial, original and scientific and technological papers on the development and peaceful application of nuclear, radiation and radionuclide techniques in chemistry, physics, biochemistry, biology, medicine, security, engineering and in the earth, planetary and environmental sciences, all including dosimetry. Nuclear techniques are defined in the broadest sense and both experimental and theoretical papers are welcome. They include the development and use of α- and β-particles, X-rays and γ-rays, neutrons and other nuclear particles and radiations from all sources, including radionuclides, synchrotron sources, cyclotrons and reactors and from the natural environment. The journal aims to publish papers with significance to an international audience, containing substantial novelty and scientific impact. The Editors reserve the rights to reject, with or without external review, papers that do not meet these criteria. Papers dealing with radiation processing, i.e., where radiation is used to bring about a biological, chemical or physical change in a material, should be directed to our sister journal Radiation Physics and Chemistry.