• Proceedings of the Korean Radioactive Waste Society Conference
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• 2010.05a
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• pp.51-52
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• 2010

• Proceedings of the Korean Nuclear Society Conference
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• 2001.05a
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• pp.424.2-424
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• 2001

• Proceedings of the Korean Nuclear Society Conference
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• 2003.05a
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• pp.294.1-294.1
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• 2003

• Proceedings of the Korean Nuclear Society Conference
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• 2003.05a
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• pp.335.1-335.1
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• 2003

• Proceedings of the KTCVS Conference
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• 1993.06a
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• pp.50-50
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• 1993

• Journal of radiological science and technology
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• v.43 no.5
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• pp.337-341
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• 2020

Although the screening with a mammography has been shown to be economical, simple and effective in detecting breast cancer, it is accompanied by the risk from radiation. Therefore, this study analyzed the glandular dose and organ dose according to the target-filter combination and the presence and absence of implants using Monte Carlo simulation. The results indicate that at a tube voltage of 30 kV and a tube current of 50 mAs, the dose increased in the order of Mo/Mo. Mo/Rh, Rh/Rh and W/Rh in proportion to the atomic number of the target-filter. In addition, in phantom without implant a reduction in dose was seen when compared to the phantom with implant. The organ dose was highest in the lens except for the breast on the examination side regardless of the presence or absence of the implant. These results may contribute to use basic data for the diagnostic reference level of breast plastic surgery patients.

• Journal of radiological science and technology
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• v.43 no.6
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• pp.461-467
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• 2020

In the field of nuclear medicine, errors are sometimes generated because the assessment of the uniformity of gamma cameras relies on the naked eye of the evaluator. To minimize these errors, we created an artificial intelligence model based on CNN algorithm and wanted to assess its usefulness. We produced 20,000 normal images and partial cold region images using Python, and conducted artificial intelligence training with Resnet18 models. The training results showed that accuracy, specificity and sensitivity were 95.01%, 92.30%, and 97.73%, respectively. According to the results of the evaluation of the confusion matrix of artificial intelligence and expert groups, artificial intelligence was accuracy, specificity and sensitivity of 94.00%, 91.50%, and 96.80%, respectively, and expert groups was accuracy, specificity and sensitivity of 69.00%, 64.00%, and 74.00%, respectively. The results showed that artificial intelligence was better than expert groups. In addition, by checking together with the radiological technologist and AI, errors that may occur during the quality control process can be reduced, providing a better examination environment for patients, providing convenience to radiologists, and improving work efficiency.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.270-277
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• 2023

Exposure to ionizing radiation induces free radicals in human nails. These free radicals generate a radiation-induced signal (RIS) in electron paramagnetic resonance (EPR) spectroscopy. Compared with the RIS of tooth enamel samples, that in human nails is more affected by moisture and heat, but has the advantages of being sensitive to radiation and easy to collect. The fingernail as a biological sample is applicable in retrospective dosimetry in cases of localized hand exposure accidents. In this study, the dosimetric characteristics of fingernails were analyzed in fingernail clippings collected from Korean donors. The dose response, fading of radiation-induced and mechanically induced signals, treatment method for evaluation of background signal, minimum detectable dose, and minimum detectable mass were investigated to propose a fingernail-EPR dosimetry protocol. In addition, to validate the practicality of the protocol, blind and field experiments were performed in the laboratory and a non-destructive testing facility. The relative biases in the dose assessment result of the blind and field experiments were 8.43% and 21.68% on average between the reference and reconstructed doses. The results of this study suggest that fingernail-EPR dosimetry can be a useful method for the application of retrospective dosimetry in cases of radiological accidents.

• Nuclear Engineering and Technology
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• v.50 no.5
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• pp.627-638
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• 2018

This article describes an integrated Level 1-Level 2 probabilistic risk assessment (PRA) methodology to evaluate the radiological risk during postulated accident scenarios initiated during the decommissioning phase of a typical Mark I containment boiling water reactor. The fuel damage scenarios include those initiated while the reactor is permanently shut down, defueled, and the spent fuel is located into the spent fuel storage pool. This article focuses on the integrated Level 1-Level 2 PRA aspects of the analysis, from the beginning of the accident to the radiological release into the environment. The integrated Level 1-Level 2 decommissioning PRA uses event trees and fault trees that assess the accident progression until and after fuel damage. Detailed deterministic severe accident analyses are performed to support the fault tree/event tree development and to provide source term information for the various pieces of the Level 1-Level 2 model. Source terms information is collected from accidents occurring in both the reactor pressure vessel and the spent fuel pool, including simultaneous accidents. The Level 1-Level 2 PRA model evaluates the temporal and physical changes in plant conditions including consideration of major uncertainties. The goal of this article is to provide a methodology framework to perform a decommissioning Probabilistic Risk Assessment (PRA), and an application to a real case study is provided to show the use of the methodology. Results will be derived from the integrated Level 1-Level 2 decommissioning PSA event tree in terms of fuel damage frequency, large release frequency, and large early release frequency, including uncertainties.

• Journal of the Korean Society of Radiology
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• v.17 no.4
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• pp.565-572
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• 2023

This study was conducted to analyze the status radiological imaging examinations assessment in Korea medical institutions conducted in the public sector and suggest a direction for improvement. Among the assessment of medical institutions, the main assessment related to radiographic imaging examinations are the certification evaluation of medical institutions and the adequacy assessment of radiographic imaging examinations. The certification evaluation of medical institutions evaluates the image inspection operation process, provision of accurate results, and compliance with safety management procedures. In the assessment of adequacy of radiographic imaging examinations, structural indicators related to manpower and equipment, patient evaluation implementation rate, and exposure reduction programs were included. However, for safer and higher-quality radiological imaging examinations, it is necessary to increase the participation rate of medical institutions in certification evaluations. In addition, it is necessary to improve the manpower indicator, and incentive payments can be considered to induce quality improvement of medical institutions in the future. Integrated management of radiation exposure at the national level should also be carried out simultaneously.