• Journal of the Korean Society of Radiology
• /
• v.10 no.1
• /
• pp.1-6
• /
• 2016

Recently, the various digital X-ray imaging devices using CCD and TFT LCD-based flat panel digital X-ray sensor are being used. In particular, a number of studies on photon counting sensor technique have been reported. In this study, the incident X-rays fluence on the photon counting sensor material was measured to estimate photon detection efficiency which is the quantitative performance evaluation factor of photon counting sensor. The result of measuring the photon fluence by using RQA-M2 Radiation beam quality of IEC 61223-1-2 recommendations, the incident photon fluence could be defined as about $4 photons/(0.01mm)^2{\cdot}{\mu}Gy$ within $10{\mu}m$ pin-hole area, and about $50photons/(0.03mm)^2{\cdot}{\mu}Gy$ within $30{\mu}m$ pin-hole area, and about $698photons/(0.1mm)^2{\cdot}{\mu}Gy$ within $100{\mu}m$ pin-hole area. Consequently, with the previously setup of the incident fluence, the measuring of actual photon counting efficiency by observing the output waveform of the photon counting sensor material was considered possible.

• Journal of the Korean Society of Radiology
• /
• v.11 no.2
• /
• pp.87-94
• /
• 2017

Monte Carlo simulations were used to assess dose enhancement effects for 60-, 90-, 120-, and 150-kV X-rays, and for 6- and 15-MV X-rays. The MCNPX code was used for a computer simulation of the ICRU slab phantom, and gold, gadolinium, and iron oxide (Fe2O3) were employed as dose enhancement agents. In consideration of the buildup region of the incident energy, agent concentrations of 5, 10, 15, and 20 mg/g were inserted on the surface of the phantom at a depth of 5 cm. Based on baseline values obtained in the absence of dose enhancement agents, a quantitative analysis was performed by evaluating depth-dependent changes in the absorbed energy and the dose enhancement factor (DEF). A higher concentration of dose enhancement agents led to a greater dose enhancement effect with iron oxide, gadolinium, and gold in descending order. For kilovoltage (kV) X-rays, as the incident energy was decreased and as the energy became closer to the ionization potential of the atoms in the enhancement agent, the dose enhancement effect increased. In the megavoltage (MV) X-ray range, dose enhancement was higher at 6 MV compared with 15 MV. However, the overall dose enhancements were significantly lower compared to the results obtained with kV X-rays.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2014.02a
• /
• pp.372-372
• /
• 2014

반도체 검출기는 입사되는 X선 에너지에 의하여 이온화되어 발생하는 전자 전공쌍을 수집함으로 방사선 정보를 확인하는 선량계로써 많은 연구와 활용이 이루어지고 있다. 하지만, X선 에너지에 의하여 반도체 검출기에서 발생하는 전기적 신호량이 높지 않기 때문에 누설 전류의 저감이 필수적이다. 누설 전류를 저감시키기 위한 방안으로 반도체 층과 전극 층의 Schottky Contact 구조의 설계, Insulating Layer의 사용, 높은 비저항의 반도체 물질 연구 등이 이루어지고 있다. 하지만, 기존에 누설 전류 저감을 위하여 Insulating Layer를 전극층과 반도체 층 사이에 형성하는 연구에 있어서 Insulating Layer와 반도체 층의 계면 사이에서 발생하는 Charge Trapping으로 인하여 생성되는 신호의 Reproducibility 저하, 동영상 적용의 제한 등의 문제점을 겪어왔다. 이에 본 논문에서는 누설 전류를 저감시킴과 동시에 Charge Trapping의 최소화를 이루기 위하여 Insulating Layer의 두께 최적화 연구를 수행하였다. 본 연구에서 사용한 Insulating Layer는 검출기 표면에 입사하는 X선 정보 손실을 최소화 시키는 동시에 누설 전류와 Charge Trapping을 최소화 시키는 방법으로써 CVD방법으로 검출기 표면에 균일하게 Insulating Layer를 코팅하였다. Insulating 물질은 Parylene을 사용하였으며, 그 중 온도, 습도 등 외부환경에 영향을 적게 받는 type C를 사용하였다. 증착에 사용한 장비의 진공도는 Torr로 설정하여 증착되는 Parylene의 두께가 약 $0.3{\mu}m$가 되게 하였으며, 실험에는 반도체 물질 PbO를 사용하였다. Parylene의 절연 특성은 Dark Current와 Sensitivity를 측정한 SNR을 이용하여 Parylene코팅이 되지 않은 동일 반도체 검출기와의 신호를 비교하였으며 또한 Parylene를 다층 제작한 검출기의 수집 신호량을 비교하였다. 제작한 검출기의 X선 조사 시의 수집 전하량 측정 결과, 100 kVp, 100mA, 0.03s의 X선 조건에서 $1V/{\mu}m$의 기준 시, Parylene를 코팅하지 않은 PbO 검출기의 Dark current는 0.0501 nA/cm2, Sensitivity는 0.6422 nC/mR-cm2, SNR은 12.184이었으며, Parylene단층의 두께인 $0.3{\mu}m$로 증착된 시편의 Dark current는 0.04097 nA/cm2, Sensitivity는 0.53732 nC/mR-cm2으로 Dark current가 감소되고 sensitivity도 감소하였지만 SNR은 13.1150으로 높아진 것을 확인할 수 있었다. Perylene이 $0.6{\mu}m$로 증착된 시편의 경우, Dark Current는 0.04064 nA/cm2, Sensitivity는 0.31473 nC/mR-cm2, SNR은 7.7443으로써 Insulating Layer가 없는 시편보다 SNR이 약 40% 낮아진 것을 확인할 수 있었다. Parylene이 $0.9{\mu}m$로 증착된 시편의 경우 Dark current는 0.0378 nA/cm2, Sensitivity 0.0461 nC/mR-cm2로 Insulating Layer가 없는 시편에 비해 SNR은 약 1/12배 감소한 1.2196이었고, Parylene이 $1.2{\mu}m$로 증착된 시편의 SNR은 1.1252로서 더 감소하였다. 따라서 Parylene을 다층 코팅한 검출기일수록 절연 효과의 영향이 커짐으로써 SNR 비교 시 수집되는 신호량이 줄어드는 것을 확인하였다. 반도체 검출기의 누설 전류를 저감시킴과 동시에 신호 수집율에 영향을 최소화시키기 위하여 Insulating Layer의 두께를 적절하게 설정하여 적용하면 Insulating Layer가 없는 검출기에 비해 누설전류를 최소한으로 줄일 수 있고 신호 검출효율이 감소하는 것을 방지할 수 있을 것이라 사료된다.

• The Journal of the Convergence on Culture Technology
• /
• v.6 no.4
• /
• pp.789-795
• /
• 2020

Many deaths have been reported due to the worldwide pandemic of COVID-19. In order to prevent the further spread of COVID-19, it is necessary to quickly and accurately read images of suspected patients and take appropriate measures. To this end, this paper introduces a deep learning-based COVID-19 chest X-ray reading technique that can assist in image reading by providing medical staff whether a patient is infected. First of all, in order to learn the reading model, a sufficient dataset must be secured, but the currently provided COVID-19 open dataset does not have enough image data to ensure the accuracy of learning. Therefore, we solved the image data number imbalance problem that degrades AI learning performance by using a Stacked Generative Adversarial Network(StackGAN++). Next, the DenseNet-based classification model was trained using the augmented data set to develop the reading model. This classification model is a model for binary classification of normal chest X-ray and COVID-19 chest X-ray, and the performance of the model was evaluated using part of the actual image data as test data. Finally, the reliability of the model was secured by presenting the basis for judging the presence or absence of disease in the input image using Grad-CAM, one of the explainable artificial intelligence called XAI.

• Journal of the Korean Magnetics Society
• /
• v.22 no.4
• /
• pp.125-129
• /
• 2012

By employing soft x-ray absorption spectroscopy (XAS) and soft x-ray magnetic circular dichroism (XMCD), the electronic structures of molecule-based nano bioparticles, such as Helicobacter pylori ferritin (H. pylori ferritin), Heme, $NaM[Fe(CN)_6]{\cdot}H_2O$-type Prussian Blue (M=Co, Ni) analogue, have been investigated. The measured Fe 2p XAS spectra reveal that Fe ions are trivalent ($Fe^{3+}$) in H. pylori ferritins, while they are in the $Fe^{2+}-Fe^{3+}$ mixed-valent states in $NaM[Fe(CN)_6]{\cdot}H_2O$ Prussian Blue analogues (M=Co, Ni). According to the Fe 2p XMCD spectrum of high-state H. pylori ferritin, all the $Fe^{3+}$ ions have the same local symmetry and their magnetic moments are aligned in the same direction. It is also found that the Fe 3d orbitals in $NaM[Fe(CN)_6]{\cdot}H_2O$ have a strong covalent bonding to $(CN)^-$ ligands, but with a very weak bonding to the 2p orbitals of O ligands.

• Journal of the Korean Society of Radiology
• /
• v.15 no.4
• /
• pp.547-554
• /
• 2021

In order to quickly and accurately diagnose pneumonia on a chest X-ray image, different batch sizes of 4, 8, 16, and 32 were applied to the same Xception deep learning model, and modeling was performed 3 times, respectively. As a result of the performance evaluation of deep learning modeling, in the case of modeling to which batch size 32 was applied, the results of accuracy, loss function value, mean square error, and learning time per epoch showed the best results. And in the accuracy evaluation of the Test Metric, the modeling applied with batch size 8 showed the best results, and the precision evaluation showed excellent results in all batch sizes. In the recall evaluation, modeling applied with batch size 16 showed the best results, and for F1-score, modeling applied with batch size 16 showed the best results. And the AUC score evaluation was the same for all batch sizes. Based on these results, deep learning modeling with batch size 32 showed high accuracy, stable artificial neural network learning, and excellent speed. It is thought that accurate and rapid lesion detection will be possible if a batch size of 32 is applied in an automatic diagnosis study for feature extraction and classification of pneumonia in chest X-ray images using deep learning in the future.

• Journal of the Korean Society of Radiology
• /
• v.15 no.4
• /
• pp.455-461
• /
• 2021

Cardiomegaly is one of the most common diseases seen on chest X-rays, but if it is not detected early, it can cause serious complications. In view of this, in recent years, many researches on image analysis in which deep learning algorithms using artificial intelligence are applied to medical care have been conducted with the development of various science and technology fields. In this paper, we would like to evaluate whether the Inception V3 deep learning model is a useful model for the classification of Cardiomegaly using chest X-ray images. For the images used, a total of 1026 chest X-ray images of patients diagnosed with normal heart and those diagnosed with Cardiomegaly in Kyungpook National University Hospital were used. As a result of the experiment, the classification accuracy and loss of the Inception V3 deep learning model according to the presence or absence of Cardiomegaly were 96.0% and 0.22%, respectively. From the research results, it was found that the Inception V3 deep learning model is an excellent deep learning model for feature extraction and classification of chest image data. The Inception V3 deep learning model is considered to be a useful deep learning model for classification of chest diseases, and if such excellent research results are obtained by conducting research using a little more variety of medical image data, I think it will be great help for doctor's diagnosis in future.

• Korean Journal of Mineralogy and Petrology
• /
• v.35 no.4
• /
• pp.457-467
• /
• 2022

Electron bombardment to silicate glass during electron probe microanalysis (EPMA) causes outward migration of Na from the excitation volume and subsequent decrease in the measured X-ray count rates of Na. To acquire precise Na₂O content of silicate glass, one should use proper analytical technique to avoid or minimize Na migration effect or should correct for decreases in the measured Na X-ray counts. In this study, we analyzed 8 silicate glass standard samples using automated Time Dependent Intensity (TDI) correction method of Probe for EPMA software that can calculate zero-time intercept by extrapolating X-ray count changes over analysis time. We evaluated an accuracy of TDI correction for Na measurements of silicate glasses with EPMA at 15 kV acceleration voltage and 20 nA probe current electron beam, which is commonly utilized analytical condition for geological samples. Results show that Na loss can be avoided with 20 ㎛-sized large beam (<0.1 nA/㎛²), thus silicate glasses can be analyzed without TDI correction. When the beam size is smaller than 10 ㎛, Na loss results in large relative errors up to -55% of Na₂O values without correction. By applying TDI corrections, we can acquire Na₂O values close to the reference values with relative errors of ~ ±10%. Use of weighted linear-fit can reduce relative errors down to ±6%. Thus, quantitative analysis of silicate glasses with EPMA is required for TDI correction for alkali elements such as Na and K.

• The Korean Journal of Nuclear Medicine
• /
• v.28 no.2
• /
• pp.206-213
• /
• 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
• /
• v.27 no.4
• /
• pp.55-60
• /
• 2004

The purpose of this study was to examine both patient exposure dose during mammography and the utility status of mammograpy equipments. The data of this study were collected through questionnaire survey for 278 medical facilities registered at Korean Hospital Association and finally 161 medical facilities's data were analyzed. According to data analysis, medical facilities of 14.9% used the average glandular dose of less than 0.5 mGy, $0.51{\sim}1.0\;mGy$ 8.6%, $1.01{\sim}1.5\;mGy$ 14.9%, $1.51{\sim}2.0\;mGy$ 11.1%, $2.01{\sim}2.5\;mGy$ 9.8%, $2.51{\sim}3.0\;mGy$ 33.3%, and 7.4% more than 3.01 mGy. It was found that medical facilities of 92.6% used less than 3 mGy, showing that this figure is similar to the limit value of 3 mGy recommended by Korea Food & Drug Administration(KFDA). Recently, international organizations such as ICRP associated with radiation protection suggests that less than 3 mGy of average mammary gland dose be used during mammography in case of using Mo target+Mo filter, film/screen system and craniocaudal projection with the breast pressed to 4.2 cm. The standard dose is being strictly observed and that of the limits is going down to 2 mGy or 1.5 mGy. The major results of this study indicate that interests and a counterplan to reduce patient dose during mammography should be considered. Based on this study, the authors of this study will continue to measure exposure dose to set a new standard for patient exposure dose during mammography.