A peak detection in noisy spectrum using principal component analysis

Eungi Min, Mincheol Ko, Yongkwon Kim, Jinhun Joung, Kisung Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

A spectrum of a radio isotope (RI) contains a single or multiple photo-peaks and radio-activities of all energy levels. These characteristics of each RI source are measured by radiation monitor (RM) systems. However, if the radiation count is extremely low and source to detector distance is too far, we cannot acquire good spectroscopic results for RI identification by RM devices while we still able to measure some counting statistics. Thus, precise peak detection in noisy spectrums is one of the most important tasks in the RM system. In this study, we developed an accurate peak detection method based on wavelet decomposition followed by principal component analysis. We used a discrete wavelet transform (DWT) for reduction of unnecessary high frequency noises in low counts spectrums. To reduce effect of a background radiation, we made a background template using a pre-measured background spectrum and calculated square errors for suppressing a background of low energy levels and maintaining true photo-peaks. Finally, we analyzed pre-processed data and detected photo-peaks using PCA. We measured Cesium 137(Cs-137) and Barium 133(Ba-133) with 1 and 10 micro curies collected from the various distance. Each spectrum was collected for a second and total 60 sets were stored for each isotope. Results of our research show that the proposed algorithm achieves high sensitivity and specificity, proving that the algorithm is appropriate for RM systems.

Original languageEnglish
Title of host publicationIEEE Nuclear Science Symposium Conference Record
Pages62-65
Number of pages4
DOIs
Publication statusPublished - 2012 Dec 1
Event2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record, NSS/MIC 2012 - Anaheim, CA, United States
Duration: 2012 Oct 292012 Nov 3

Other

Other2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record, NSS/MIC 2012
CountryUnited States
CityAnaheim, CA
Period12/10/2912/11/3

Fingerprint

principal components analysis
Principal Component Analysis
Radio
photopeak
Isotopes
Radiation
monitors
isotopes
radiation
energy levels
cesium 137
Background Radiation
Wavelet Analysis
Cesium
Passive Cutaneous Anaphylaxis
background radiation
Barium
radioactivity
wavelet analysis
barium

ASJC Scopus subject areas

  • Radiation
  • Nuclear and High Energy Physics
  • Radiology Nuclear Medicine and imaging

Cite this

Min, E., Ko, M., Kim, Y., Joung, J., & Lee, K. (2012). A peak detection in noisy spectrum using principal component analysis. In IEEE Nuclear Science Symposium Conference Record (pp. 62-65). [6551061] https://doi.org/10.1109/NSSMIC.2012.6551061

A peak detection in noisy spectrum using principal component analysis. / Min, Eungi; Ko, Mincheol; Kim, Yongkwon; Joung, Jinhun; Lee, Kisung.

IEEE Nuclear Science Symposium Conference Record. 2012. p. 62-65 6551061.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Min, E, Ko, M, Kim, Y, Joung, J & Lee, K 2012, A peak detection in noisy spectrum using principal component analysis. in IEEE Nuclear Science Symposium Conference Record., 6551061, pp. 62-65, 2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record, NSS/MIC 2012, Anaheim, CA, United States, 12/10/29. https://doi.org/10.1109/NSSMIC.2012.6551061
Min E, Ko M, Kim Y, Joung J, Lee K. A peak detection in noisy spectrum using principal component analysis. In IEEE Nuclear Science Symposium Conference Record. 2012. p. 62-65. 6551061 https://doi.org/10.1109/NSSMIC.2012.6551061
Min, Eungi ; Ko, Mincheol ; Kim, Yongkwon ; Joung, Jinhun ; Lee, Kisung. / A peak detection in noisy spectrum using principal component analysis. IEEE Nuclear Science Symposium Conference Record. 2012. pp. 62-65
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