• Journal of Periodontal and Implant Science
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• v.47 no.1
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• pp.20-29
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• 2017

Purpose: The microstructural characteristics of trabecular bone were identified using micro-computed tomography (micro-CT), in order to develop a potential strategy for implant surface improvement to facilitate osseointegration. Methods: Alveolar bone specimens from the cadavers of 30 humans were scanned by high-resolution micro-CT and reconstructed. Volumes of interest chosen within the jaw were classified according to Hounsfield units into 4 bone quality categories. Several structural parameters were measured and statistically analyzed. Results: Alveolar bone specimens with D1 bone quality had significantly higher values for all structural parameters than the other bone quality categories, except for trabecular thickness (Tb.Th). The percentage of bone volume, trabecular separation (Tb.Sp), and trabecular number (Tb.N) varied significantly among bone quality categories. Tb.Sp varied markedly across the bone quality categories (D1: $0.59{\pm}0.22mm$, D4: $1.20{\pm}0.48mm$), whereas Tb.Th had similar values (D1: $0.30{\pm}0.08mm$, D4: $0.22{\pm}0.05mm$). Conclusions: Bone quality depended on Tb.Sp and number-that is, endosteal space architecture-rather than bone surface and Tb.Th. Regardless of bone quality, Tb.Th showed little variation. These factors should be taken into account when developing individualized implant surface topographies.

• Journal of the Korea Safety Management & Science
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• v.12 no.2
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• pp.225-230
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• 2010

The purpose of the study was to apply and to expand the six sigma to reduce waiting times for computed tomography (CT) examination which manipulated by the department of radiology. It was preceded by DMAIC (Define, Measure, Analyze, Improve, and Control). In the stage of definition, it wereselected for total 5 critical to quality (CTQ), which were the kindness, the waiting time, the examination explanation, the waiting day and the waiting stand environment, that increased the reserved time of CT examination. In the stage of measurement, the number of examinations and of reservation waiting days performed and resulted in final CTQ(Y) which measured each 1.68 and 1.85 sigma. In the stage of analysis, the examination concentrated on morning time, non-scheduled examination of the day, the delayed time of booking, frequent telephone contacting and equipment malfunction were determined as variable key causes. In the stage of improvement, it were performed with expansion of the examination in the morning time, integration of laboratories that used to in each steps, developing the ability of simultaneous booking schedule for the multiple examinations, developing program of examination request, and the customer management team operations. For the control, the number of examinations and reserved waiting days were measured each 3.14 and 1.13 sigma.

• Journal of Medicine and Life Science
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• v.20 no.3
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• pp.107-114
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• 2023

Epidemiological control of coronavirus disease 2019 (COVID-19) is needed to estimate the infection period of confirmed cases and identify potential cases. The present study, targeting confirmed cases for which the time of COVID-19 symptom onset was disclosed, aimed to investigate the relationship between intervals (day) from symptom onset to testing the cycle threshold (CT) values of real-time reverse transcription-polymerase chain reaction. Of the COVID-19 confirmed cases, those for which the date of suspected symptom onset in the epidemiological investigation was specifically disclosed were included in this study. Interval was defined as the number of days from symptom onset (as disclosed by the patient) to specimen collection for testing. A locally weighted regression smoothing (LOWESS) curve was applied, with intervals as explanatory variables and CT values (CTR for RdRp gene and CTE for E gene) as outcome variables. After finding its non-linear relationship, a polynomial regression model was applied to estimate the 95% confidence interval values of CTR and CTE by interval. The application of LOWESS in 331 patients identified a U-shaped curve relationship between the CTR and CTE values according to the number of interval days, and both CTR and CTE satisfied the quadratic model for interval days. Active application of these results to epidemiological investigations would minimize the chance of failing to identify individuals who are in contact with COVID-19 confirmed cases, thereby reducing the potential transmission of the virus to local communities.

• Nuclear Engineering and Technology
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• v.56 no.10
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• pp.4355-4364
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• 2024

Fluid pipelines, commonly utilized in the oil industry, often face efficiency and reliability issues due to sediment buildup causing erosion, corrosion, and pipe wall thinning. Traditional assessment methods involve disruptive measures like cutting or creating holes and temporarily taking pipelines out of service. A non-destructive alternative, Limited-Number-Detector Computed Tomography (LNDCT), proves cost-effective and superior. Our proposed algorithm enhances data acquisition and projections using discrete detectors, employing Co-60 as a gamma-ray source and thallium-doped sodium iodide, NaI(Tl), detectors in an arc configuration. Monte Carlo simulations aligned closely with experimental data. Optimization involved adjusting the detector aperture angle based on a primary-to-scatter ratio of gamma-ray photons. We investigated the utility of various isotopes (Co-60, Cs-137, Am-241, Ir-192) to determine optimal projection signal amplitude. The algorithm generates a large sinogram matrix, and a filtered back-projection algorithm with a Hamming filter maximizes image quality while ensuring acceptable calculation volume and time. Using four phantoms, including pipelines filled to different scales, our study evaluates LNDCT configuration, performance, and validation. The results highlight its potential for efficiently evaluating sediment in pipelines, confirming the correctness and accuracy of our proposed algorithm.

• Progress in Medical Physics
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• v.21 no.2
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• pp.137-144
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• 2010

The purpose of this study was to evaluate the usefulness of reducing of craniofacial radiation dose using automatic exposure control (AEC) technique in the 64 multi-detector computed tomography (MDCT). We used SOMATOM Definition 64 multi-detector CT, and head of whole body phantom (KUPBU-50, Kyoto Kagaku CO. Ltd). The protocol were helical scan method with 120 kVp, 1 sec of rotation time, 5 mm of slice thickness and increment, 250 mm of FOV, $512{\times}512$ of matrix size, $64{\times}0.625\;mm$ of collimation, and 1 of pitch. The evaluation of dose reducing effect was compared the fixed tube current of 350 with AEC technique. The image quality was measured the noise using standard deviation of CT number. The range of craniofacial bone was to mentum end from calvaria apex, which devided three regions: calvaria~superciliary ridge (1 segment), superciliary ridge~acanthion (2 segment), and acanthion~mentum (3 segment). In the fixed tube current technique, CTDIvol was 57.7 mGy, DLP was $640.2\;mGy{\cdot}cm$ in the all regions. The AEC technique was showed that 1 segment were 30.7 mGy of CTDIvol, 340.7 $mGy{\cdot}cm$ of DLP, 2 segment were 46.5 mGy of CTDIvol, $515.0\;mGy{\cdot}cm$ of DLP, and 3 segment were 30.3 mGy of CTDIvol, $337.0\;mGy{\cdot}cm$ of DLP. The standard deviation of CT number was 2.622 with the fixed tube current technique and 3.023 with the AEC technique in the 1 segment, was 3.118 with the fixed tube current technique and 3.379 with the AEC technique in the 2 segment, was 2.670 with the fixed tube current technique and 3.186 with the AEC technique in the 3 segment. The craniofacial radiation dose using AEC Technique in the 64 MDCT was evaluated the usefulness of reducing for the eye, the parotid and thyroid with high radiation sensitivity particularly.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.794-798
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• 2009

We introduce an implementation of plug-ins on PLUTO. These plug-ins discriminate inflammatory nodules from other types of nodules in chest X-ray CT images. The PLUTO is a common platform for computer-aided diagnosis systems on Microsoft Windows series and it is easy to add new functions as plug-ins. We coded two plug-ins. One of the them calculates features based on medical knowledge. The other plug-in calculates parameters to classify the type of nodules, and it also classifies nodules into inflammatory nodules and others using SVM. These plug-ins are coded using MIST library which is produced at Nagoya University, Japan. In our previous study, the MIST library was parallelized, so that we can utilize a number of CPUs to calculate features and SVM learning/classifying depending on the amount of computation. Using these plug-ins, it became easy to extract features to discriminate inflammatory nodules from other types of nodules and to change parameters for feature extraction and SVM learning/classifying with GUI interface. The accuracy of the classifying result is 100% with 78 solid nodules which contains 43 inflammatory nodules and 35 other type of nodules.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7C
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• pp.601-609
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• 2012

In this paper, a limited-view CT image reconstruction method was studied to reduce the scan times and the X-ray dose for the patients. To reduce streak artifacts which is caused by insufficient number of views, we introduce a sinogram interpolation method based on image matching. Image matching is achieved using the characteristics of the neighboring views including intensity, gradient and distance between the pixels. Interpolation is performed using the image matching results.. A numerical phantom and Al-acryl phantom were used for evaluating the effectiveness of the proposed interpolation method. The results showed that streak artifacts were reduced in the reconstructed images while the details of the images were preserved. Moreover, maximum 5% improvements in terms of PSNR were observed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.5
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• pp.755-765
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• 2015

This paper is concerned with Interval Type-2 Radial Basis Function Neural Network classifier realized with the aid of Census Transform(CT) and (2D)2LDA methods. CT is considered to improve performance of face recognition in a variety of illumination variations. (2D)2LDA is applied to transform high dimensional image into low-dimensional image which is used as input data to the proposed pattern classifier. Receptive fields in hidden layer are formed as interval type-2 membership function. We use the coefficients of linear polynomial function as the connection weights of the proposed networks, and the coefficients and their ensuing spreads are learned through Conjugate Gradient Method(CGM). Moreover, the parameters such as fuzzification coefficient and the number of input variables are optimized by Artificial Bee Colony(ABC). In order to evaluate the performance of the proposed classifier, Yale B dataset which consists of images obtained under diverse state of illumination environment is applied. We show that the results of the proposed model have much more superb performance and robust characteristic than those reported in the previous studies.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.292-300
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• 2024

Kinetic simulations have been performed on an Inertial Electrostatic Confinement Fusion (IECF) device. These simulations were performed using the particle-in-cell (PIC) method to analyze the behavior of ions in an IEC device and the effects of some parameters on the Confinement Time (CT). CT is an essential factor that significantly contributes to the IEC's performance as a nuclear fusion device. Using the PIC method, the geometry of a two-grided device with variable grid radius, the number of cathode grid rings, variable pressure and different dielectric thickness for the feed stalk was simulated. In this research, with the development of previous works, the interaction of particles was simulated and compared with previous results. The simulation results are in good agreement with the previous results. In these simulations, it was found that with the increase of the dielectric thickness of the feed stalk, the electric field was weakened and as a result, the confinement time was reduced. On the other hand, with the increase of the cathode radius, the confinement time increased. Using the results, an IEC device can be designed with higher efficiency and more optimal CT for ions.

• Korean Journal of Radiology
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• v.21 no.7
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• pp.838-850
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• 2020

Computed tomography (CT) is an important imaging modality in evaluating thoracic malignancies. The clinical utility of dual-energy spectral computed tomography (DESCT) has recently been realized. DESCT allows for virtual monoenergetic or monochromatic imaging, virtual non-contrast or unenhanced imaging, iodine concentration measurement, and effective atomic number (Z_eff map). The application of information gained using this technique in the field of thoracic oncology is important, and therefore many studies have been conducted to explore the use of DESCT in the evaluation and management of thoracic malignancies. Here we summarize and review recent DESCT studies on clinical applications related to thoracic oncology.