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Research on Calculation Method of Radiation Response Eigenvalue of a Single-Chip Active Pixel Sensor

In this paper, we present a calculation method for the radiation response eigenvalue based on a monolithic active pixel sensor. By comparing the statistical eigenvalues of different regions of a pixel array in bright and dark environments, the linear relationship between the statistical eigenvalues...

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Autores principales: Qin, Zhiwei, Xu, Shoulong, Dong, Hanfeng, Han, Yongchao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269208/
https://www.ncbi.nlm.nih.gov/pubmed/35808311
http://dx.doi.org/10.3390/s22134815
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author Qin, Zhiwei
Xu, Shoulong
Dong, Hanfeng
Han, Yongchao
author_facet Qin, Zhiwei
Xu, Shoulong
Dong, Hanfeng
Han, Yongchao
author_sort Qin, Zhiwei
collection PubMed
description In this paper, we present a calculation method for the radiation response eigenvalue based on a monolithic active pixel sensor. By comparing the statistical eigenvalues of different regions of a pixel array in bright and dark environments, the linear relationship between the statistical eigenvalues obtained by different algorithms and the radiation dose rate was studied. Additionally, a dose rate characterization method based on the analysis of the eigenvalues of the MAPS response signal was proposed. The experimental results show that in the dark background environment, the eigenvalues had a good linear response in the region of any gray value in the range of 10–30. In the color images, due to the difference in the background gray values in adjacent color regions, the radiation response signal in dark regions was confused with the image information in bright regions, resulting in the loss of response signal and affecting the analysis results of the radiation response signal. For the low dose rate radiation field, as the radiation response signal was too weak and there was background dark noise, it was necessary to accumulate frame images to obtain a sufficient response signal. For the intense radiation field, the number of response events in a single image was very high, and only two consecutive frames of image data needed to be accumulated to meet the statistical requirements. The binarization method had a good characterization effect for the radiation at a low dose rate, and the binarization processing and the total gray value statistics of the response data at a high dose rate could better characterize the radiation dose rate. The calibration experiment results show that the binarization processing method can meet the requirements of using a MAPS for wide-range detection.
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spelling pubmed-92692082022-07-09 Research on Calculation Method of Radiation Response Eigenvalue of a Single-Chip Active Pixel Sensor Qin, Zhiwei Xu, Shoulong Dong, Hanfeng Han, Yongchao Sensors (Basel) Article In this paper, we present a calculation method for the radiation response eigenvalue based on a monolithic active pixel sensor. By comparing the statistical eigenvalues of different regions of a pixel array in bright and dark environments, the linear relationship between the statistical eigenvalues obtained by different algorithms and the radiation dose rate was studied. Additionally, a dose rate characterization method based on the analysis of the eigenvalues of the MAPS response signal was proposed. The experimental results show that in the dark background environment, the eigenvalues had a good linear response in the region of any gray value in the range of 10–30. In the color images, due to the difference in the background gray values in adjacent color regions, the radiation response signal in dark regions was confused with the image information in bright regions, resulting in the loss of response signal and affecting the analysis results of the radiation response signal. For the low dose rate radiation field, as the radiation response signal was too weak and there was background dark noise, it was necessary to accumulate frame images to obtain a sufficient response signal. For the intense radiation field, the number of response events in a single image was very high, and only two consecutive frames of image data needed to be accumulated to meet the statistical requirements. The binarization method had a good characterization effect for the radiation at a low dose rate, and the binarization processing and the total gray value statistics of the response data at a high dose rate could better characterize the radiation dose rate. The calibration experiment results show that the binarization processing method can meet the requirements of using a MAPS for wide-range detection. MDPI 2022-06-25 /pmc/articles/PMC9269208/ /pubmed/35808311 http://dx.doi.org/10.3390/s22134815 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Qin, Zhiwei
Xu, Shoulong
Dong, Hanfeng
Han, Yongchao
Research on Calculation Method of Radiation Response Eigenvalue of a Single-Chip Active Pixel Sensor
title Research on Calculation Method of Radiation Response Eigenvalue of a Single-Chip Active Pixel Sensor
title_full Research on Calculation Method of Radiation Response Eigenvalue of a Single-Chip Active Pixel Sensor
title_fullStr Research on Calculation Method of Radiation Response Eigenvalue of a Single-Chip Active Pixel Sensor
title_full_unstemmed Research on Calculation Method of Radiation Response Eigenvalue of a Single-Chip Active Pixel Sensor
title_short Research on Calculation Method of Radiation Response Eigenvalue of a Single-Chip Active Pixel Sensor
title_sort research on calculation method of radiation response eigenvalue of a single-chip active pixel sensor
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269208/
https://www.ncbi.nlm.nih.gov/pubmed/35808311
http://dx.doi.org/10.3390/s22134815
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