• Journal of the Korean Society of Radiology
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• v.16 no.3
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• pp.303-308
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• 2022

Mammography using X-rays is currently the most used for early diagnosis of breast cancer. As the frequency of use of X-ray devices increases, interest in radiation hazards caused by mammography is increasing. Therefore, in this study, in order to measure the exposure dose of the mammary gland in X-ray mammography that requires high contrast and high resolution, the international Atomic Energy Agency (IAEA) stipulates the international standards presented by IEC 62220-1-2: 2015. Based on the beam quality criteria of the recommendation, we tried to present a guideline for evaluating the average mammary gland dose. As a result, the average streamline dose value of the 4.5 cm PMMA phantom was 2.3 mGy at the maximum within the 30 kV range, and was evaluated to be 1.19 mGy based on 28 kV.

• Progress in Medical Physics
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• v.13 no.1
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• pp.44-50
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• 2002

CsI(T1) single crystal was grown in a Bridgman growing apparatus, which has the diameter of 11 mm and the mole ratio of 0.001 mol%. Radiation sensors were made with CsITl)crystal and two photodiodes, and measured spectroscopic characteristics and linearity for gamma-ray and X-ray. The energy resolution of CsI(T1) radiation sensor has been measured with $^{22}$ Na, $^{137}$ Cs and $^{60}$ Co gamma standard sources. Also output linearity of CsITl) sensor was measured for diagnostic radiation region. The energy resolutions of CsI(T1) radiation sensor for 0.511MeV gamma-ray from Na-22 source, 0.662MeV from Cs-137 source, and 1.17MeV and 1.332MeV from Co-60 source were 13.2%, 8.3%, 6.7%, and 5.1% respectively. Also the output linearity up to 80mAs current for 60kVp, 80kvp, 100kVp, 120kVp tube voltages has been studied.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.990-992
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• 2015

X-선 영상은 소량의 방사선을 이용하여 만들어지는데 진단 결과를 빠르게 알 수 있지만 혈관이나 근육 밀도가 비슷한 구조물을 구분하는데 있어 주관적 판단이 개입된다. 따라서 영상을 보며 병변의 유무를 진단 할 때에도 정상조직과 병변조직과의 농도차이가 확연하게 들어나지 않은 경우에 환자의 상태를 정확히 진단하기 어렵다. 이러한 x선 촬영영상의 문제점이 있기에 미세한 농도의 차이를 보다 확실히 구분 지을 수 있기 때문에 영상처리가 요구된다. 특히 유선조영 촬영의 경우 주변의 연부조직과 유선의 밀도차이를 극대화시키기 위해 조영제를 유선으로 주입하여 영상을 얻는데, 미세한 병변을 놓치지 않고 객관적으로 판별을 할 수 있도록 다양한 배경영상 전처리 알고리즘의 영향을 분석하였다.

• Journal of the Korean Society of Radiology
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• v.14 no.6
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• pp.773-780
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• 2020

With the development of the 4th industrial, research is being conducted to prevent diseases and reduce damage in various fields of science and technology such as medicine, health, and bio. As a result, artificial intelligence technology has been introduced and researched for image analysis of radiological examinations. In this paper, we will directly apply a deep learning model for classification and detection of pneumonia using chest X-ray images, and evaluate whether the deep learning model of the Inception series is a useful model for detecting pneumonia. As the experimental material, a chest X-ray image data set provided and shared free of charge by Kaggle was used, and out of the total 3,470 chest X-ray image data, it was classified into 1,870 training data sets, 1,100 validation data sets, and 500 test data sets. I did. As a result of the experiment, the result of metric evaluation of the Inception V3 deep learning model was 94.80% for accuracy, 97.24% for precision, 94.00% for recall, and 95.59 for F1 score. In addition, the accuracy of the final epoch for Inception V3 deep learning modeling was 94.91% for learning modeling and 89.68% for verification modeling for pneumonia detection and classification of chest X-ray images. For the evaluation of the loss function value, the learning modeling was 1.127% and the validation modeling was 4.603%. As a result, it was evaluated that the Inception V3 deep learning model is a very excellent deep learning model in extracting and classifying features of chest image data, and its learning state is also very good. As a result of matrix accuracy evaluation for test modeling, the accuracy of 96% for normal chest X-ray image data and 97% for pneumonia chest X-ray image data was proven. The deep learning model of the Inception series is considered to be a useful deep learning model for classification of chest diseases, and it is expected that it can also play an auxiliary role of human resources, so it is considered that it will be a solution to the problem of insufficient medical personnel. In the future, this study is expected to be presented as basic data for similar studies in the case of similar studies on the diagnosis of pneumonia using deep learning.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.11-19
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• 2014

In this paper, we design an intelligent agent system with the data mining module and information fusion module as the core components of the system and investigate the possibility for the medical expert system. In the data mining module, fuzzy neural network, OFUN-NET analyzes multi-view data and produces fuzzy cluster knowledge base. In the information fusion module and application module, they serve the diagnosis result with possibility degree and useful information for diagnosis, such as uncertainty decision status or detection of asymmetry. We also present the experiment results on the BI-RADS-based feature data set selected form DDSM benchmark database. They show higher classification accuracy than conventional methods and the feasibility of the system as a computer aided diagnosis system.

• The Korean Journal of Nuclear Medicine
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• v.21 no.1
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• pp.69-73
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• 1987

외상에 의한 횡경막파열은 신속한 진단이 매우 어렵다. 이는 임상증상 및 일반적인 방사선학적 소견이 특이성이 없고, 많은 다른 외상이 동반되어 임상적으로나 방사선학적으로 진단하기 힘들기 때문이다. 더우기 외상성 청경막파열은 좌측에 비해 우측에서는 매우 드물다. 저자들은 임상경사와 단순 흉부-X선 사진상에서 진단이 어려웠던 우측 외상성 횡경막 파열등 3예에 매해서 간신티그램을 시행하여 몇가지 특징적 소견을 관찰할 수 있었다. 즉 간신티그램 상에서 관찰된 횡경막파열의 특징적인 소견은 1) 청경막 탈출에 의한 간우엽의 융기 2) 융기부 기저부의 예각형성 그리고 3) 횡경막교약에 의한 띠모양의 냉소이었다. 그러나 이들 3가지 소견은 반드시 모두가 나타나지 않을 뿐만 아니라 같은 환자에서도 신티영상의 촬영방향에 따라 나타나는 수도 있고 나타나지 않을 수도 있었다. 그러므로 우측 횡경막내 외상성파열로 인한 간 등의 허니아를 진단하기 위해서는 다각도로 신티영상 촬영을 하여야 할 것이다.

• Journal of the Korean Society of Radiology
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• v.12 no.7
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• pp.879-886
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• 2018

A 3-dimensional (D) printer is a device capable of outputting a three-dimensional solid object based on data modeled in a computer. These features are utilized in the bone model X - ray phantom production etc using CT data by fusing with the radiation science field. A bone model phantom was made using data obtained by CT scan of an existing Pelvis phantom, using PLA, Wood, XT-CF20, Glow fill, Steel filaments which are materials of Fused Filament Fabrication (FFF) 3D printer.Measure Hounsfield Unit (HU) with images obtained by CT scan of the existing Pelvis phantom and five material phantoms made with 3D printer under the same conditions,SI and SNR were measured using a diagnostic X-ray generator, and each phantom was compared and analyzed.As a result, the X - ray phantom in the X - ray examination condition of the limb was found to be most suitable for the glow fill filament.The characteristics of the filament can be known to the base of this research and the practicality of X - ray phantom fabrication was confirmed.

• Journal of the Korean Society of Radiology
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• v.82 no.6
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• pp.1524-1533
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• 2021

Purpose To investigate the incidence of tuberculosis (TB) in healthcare workers (HCWs) with positive interferon-gamma release assay (IGRA) results based on chest X-ray (CXR) and CT findings and determine the role of imaging in the diagnosis of TB. Materials and Methods Among 1976 hospital personnel screened for TB using IGRA, IGRApositive subjects were retrospectively investigated. Clustered nodular and/or linear streaky opacities in the upper lung zone were considered positive on CXR. The CT findings were classified as active, indeterminate, inactive, or normal. The active or indeterminate class was considered CT-positive. Results IGRA was positive in 255 subjects (12.9%). CXR and CT were performed in 249 (99.2%) and 113 subjects (45.0%), respectively. CXR- and CT-positive findings were found in 7 of 249 (2.8%) and 9 of 113 (8.0%) patients, respectively. Among the nine CT-positive subjects, active and indeterminate TB findings were found in 6 (5.3%) and 3 (2.7%) patients, respectively. Microbiological tests, including acid-fast bacilli staining, culture, and polymerase chain reaction for TB, were negative in all nine CT-positive subjects. Empirical anti-TB medications were administered to 9 CT-positive subjects, and 3 of these nine subjects were CXR-negative for pulmonary TB.

• The Korean Journal of Nuclear Medicine
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• v.28 no.2
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• pp.206-213
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• 1994

We studied 90 patients(179 femoral heads) with avascular necrosis of femoral head, who had been performed X-ray, bone scan and MRI to compare of the findings of AVN on bone scan between each other, retrospectively. The patients were 82 males and 9 females, their mean age was 45 years. Radiographic stages were classified by Steinberg modification, radionuclide stages were classified as followed; stage o(or type 0) : normal, stage 1 : faint ring like uptake around the femoral head, stage 2: intense ring like uptake, stage 3: irregular increased uptake with central photon defect, stage 4 : Intense diffuse increased uptake at femoral head and stage 5 : hip joint deformity with relatively mild increased uptake. The findings of MRI were classified according to extent, location, early or advanced lesion, signal intensity of the lesion and joint effusion. 156(87%) of 179 femoral heads had avascular necrosis, 68(75.5%) of 90 patients had bilateral AVN, 35 femoral heads had early stage and 120 had advanced stage. The detection rate of AVN by X-ray and bone scan were 85% (134), 91.6% (143), respectively. Early AVN with atypical types of bone scan showed larger extent, moderate to large amount of joint effusion, soft tissue hypertrophy within joint, and secondary degenerative changes. Bone scan had relatively high detection rate in the diagnosis of AVN of femoral head, and demonstrated various types depending on the disease stage.

• Journal of radiological science and technology
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• v.17 no.1
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• pp.65-70
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• 1994