• Journal of Radiation Protection and Research
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• v.40 no.2
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• pp.118-123
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• 2015

The frequency of diagnostic radiation examinations in medical institutions has recently increased to 220 million cases in 2011, and the annual exposure dose per capita was 1.4 mSv, 51% and 35% respectively, compared to those in 2007. The number of chest radiography was found to be 27.59% of them, the highest frequency of normal radiography. In this study, we developed a shielding device to minimize radiation exposure by shielding areas of the body which are unnecessary for image interpretation, during the chest radiography. And in order to verify its usefulness, we also measured the difference in entrance surface dose (ESD) and the absorbed dose, before and after using the device, by using an international standard pediatric (10 years) phantom and a glass dosimeter. In addition, we calculated the effective dose by using a Monte Carlo simulation-based program (PCXMC 2.0.1) and evaluated the reduction ratio indirectly by comparing lifetime attributable risk of cancer incidence (LAR). When using the protective device, the ESD decreased by 86.36% on average, nasal cavity $0.55{\mu}Sv$ (74.06%), thyroid $1.43{\mu}Sv$ (95.15%), oesophagus $6.35{\mu}Sv$ (78.42%) respectively, and the depth dose decreased by 72.30% on average, the cervical spine(upper spine) $1.23{\mu}Sv$ (89.73%), salivary gland $0.5{\mu}Sv$ (92.31%), oesophagus $3.85{\mu}Sv$ (59.39%), thyroid $2.02{\mu}Sv$ (73.53%), thoracic vertebrae(middle spine) $5.68{\mu}Sv$ (54.01%) respectively, so that we could verify the usefulness of the shielding mechanism. In addition, the effective dose decreased by 11.76% from $8.33{\mu}Sv$ to $7.35{\mu}Sv$ before and after wearing the device, and in LAR assessment, we found that thyroid cancer decreased to male 0.14 people (95.12%) and female 0.77 people (95.16%) per one million 10-year old children, and general cancers decreased to male 0.14 people (11.70%) and female 0.25 people (11.70%). Although diagnostic radiation examinations are necessary for healthcare such as the treatment of diseases, based on the ALARA concept, we should strive to optimize medical radiation by using this shielding device actively in the areas of the body unnecessary for the diagnosis.

• Progress in Medical Physics
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• v.25 no.4
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• pp.271-280
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• 2014

Recently, digital breast tomosynthesis (DBT) has been investigated to overcome the limitation of conventional mammography for overlapping anatomical structures and high patient dose with cone-beam computed tomography (CBCT). However incomplete sampling due to limited angle leads to interference on the neighboring slices. Many studies have investigated to reduce artifacts such as interference. Moreover, appropriate filters for tomosynthesis have been researched to solve artifacts resulted from incomplete sampling. The primary purpose of this study is finding appropriate filter scheme with FBP reconstruction for DBT system to reduce artifacts. In this study, we investigated characteristics of various filter schemes with simulation and prototype digital breast tomosynthesis under same acquisition parameters and conditions. We evaluated artifacts and noise with profiles and COV (coefficinet of variation) to study characteristic of filter. As a result, the noise with parameter 0.25 of Spectral filter reduced by 10% in comparison to that with only Ramp-lak filter. Because unbalance of information reduced with decreasing B of Slice thickness filter, artifacts caused by incomplete sampling reduced. In conclusion, we confirmed basic characteristics of filter operations and improvement of image quality by appropriate filter scheme. The results of this study can be utilized as base in research and development of DBT system by providing information that is about noise and artifacts depend on various filter schemes.

• Radiation Oncology Journal
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• v.19 no.3
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• pp.287-292
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• 2001

Prupose : We analyzed setup errors induced by using air-vacuum cushion as immobilization device in patients with rectal cancer. Materials and methods : We had treated the twenty patients with rectal cancer by 6 MV, 10 MV X-ray from Aug. 1998 to Aug. 1999 at Chungnam National University Hospital. All patients were treated at prone position. They were separated to two groups, control group, 10 patients using styrofoam, and test group, 10 patients using styrofoam and air-vacuum cushion. We measured errors of posterior field for x, y axis and lateral field for z, y axis with simulation film and EPID image using a matching technique. Results : In control group, the mean displacement values of pelvic bone landmark for x axis and y axis were 0.02 mm. 0.78 mm, respectively and the standard deviations of systematic error were 2.13 mm, 2.40 mm, respectively and the standard deviation of random error were 1.46 mm. 1.51 mm, respectively. In test group, the mean displacement values of x axis and y axis were -0.33 mm. 0.81 mm, respectively and the standard deviations of systematic error were 1.71 mm, 3.08 mm, respectively and the standard deviations of random errors were 1.40 mm. 1.88 mm, respectively. The mean displacement values of z axis and y axis were 2.98 mm. 0.74 mm, respectively and the standard deviations of systematic error were 4.75 mm, 2.65 mm, respectively and standard deviations of random error were 2.69 mm. 1.86 mm, respectively. The statistical difference of field size by using air vacuum cushion between two groups in posterior direction and lateral direction was not shown. Conclusion : We think that use of air-vacuum cushion may not be an advantage for improving setup accuracy in rectal cancer patients.

• Radiation Oncology Journal
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• v.20 no.3
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• pp.283-293
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• 2002

Purpose : A PC based brachytherapy planning system was developed to display dose distributions on simulation images by 2D isodose curve including the dose profiles, dose-volume histogram and 30 dose distributions. Materials and Methods : Brachytherapy dose planning software was developed especially for the Ir-192 source, which had been developed by KAERI as a substitute for the Co-60 source. The dose computation was achieved by searching for a pre-computed dose matrix which was tabulated as a function of radial and axial distance from a source. In the computation process, the effects of the tissue scattering correction factor and anisotropic dose distributions were included. The computed dose distributions were displayed in 2D film image including the profile dose, 3D isodose curves with wire frame forms and dosevolume histogram. Results : The brachytherapy dose plan was initiated by obtaining source positions on the principal plane of the source axis. The dose distributions in tissue were computed on a $200\times200\;(mm^2)$ plane on which the source axis was located at the center of the plane. The point doses along the longitudinal axis of the source were $4.5\~9.0\%$ smaller than those on the radial axis of the plane, due to the anisotropy created by the cylindrical shape of the source. When compared to manual calculation, the point doses showed $1\~5\%$ discrepancies from the benchmarking plan. The 2D dose distributions of different planes were matched to the same administered isodose level in order to analyze the shape of the optimized dose level. The accumulated dose-volume histogram, displayed as a function of the percentage volume of administered minimum dose level, was used to guide the volume analysis. Conclusion : This study evaluated the developed computerized dose planning system of brachytherapy. The dose distribution was displayed on the coronal, sagittal and axial planes with the dose histogram. The accumulated DVH and 3D dose distributions provided by the developed system may be useful tools for dose analysis in comparison with orthogonal dose planning.

• The Korean Journal of Nuclear Medicine
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• v.31 no.1
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• pp.19-29
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• 1997

Recently, [I-123]IPT SPECT has been used for early diagnosis of Parkinson's patients(PP) by imaging dopamine transporters. The dynamic time activity curves in basal ganglia(BG) and occipital cortex(OCC) without blood samples were obtained for 2 hours. These data were then used to measure dopamine transporters by operationally defined ratio methods of (BG-OCC)/OCC at 2 hrs, binding potential $R_v=k_3/k_4$ using graphic method or $R_A$= (ABBG-ABOCC)/ABOCC for 2 hrs, where ABBG represents accumulated binding activity in basal ganglia(${\int}^{120min}_0$ BG(t)dt) and ABOCC represents accumulated binding activity in occipital cortex(${\int}^{120min}_0$ OCC(t)dt). The purpose of this study was to examine the IPT pharmacokinetics and investigate the usefulness of simplified methods of (BG-OCC)/OCC, $R_A$, and $R_v$ which are often assumed that these values reflect the true values of $k_3/k_4$. The rate constants $K_1,\;k_2\;k_3$ and $k_4$ to be used for simulations were derived using [I-123]IPT SPECT and aterialized blood data with a standard three compartmental model. The sensitivities and time activity curves in BG and OCC were computed by changing $K_l$ and $k_3$(only BG) for every 5min over 2 hours. The values (BG-OCC)/OCC, $R_A$, and $R_v$ were then computed from the time activity curves and the linear regression analysis was used to measure the accuracies of these methods. The late constants $K_l,\;k_2\;k_3\;k_4$ at BG and OCC were $1.26{\pm}5.41%,\;0.044{\pm}19.58%,\;0.031{\pm}24.36%,\;0.008{\pm}22.78%$ and $1.36{\pm}4.76%,\;0.170{\pm}6.89%,\;0.007{\pm}23.89%,\;0.007{\pm}45.09%$, respectively. The Sensitivities for ((${\Delta}S/S$)/(${\Delta}k_3/k_3$)) and ((${\Delta}S/S$)/(${\Delta}K_l/K_l$)) at 30min and 120min were measured as (0.19, 0.50) and (0.61, 0,23), respectively. The correlation coefficients and slopes of ((BG-OCC)/OCC, $R_A$, and $R_v$) with $k_3/k_4$ were (0.98, 1.00, 0.99) and (1.76, 0.47, 1.25), respectively. These simulation results indicate that a late [I-123]IPT SPECT image may represent the distribution of the dopamine transporters. Good correlations were shown between (3G-OCC)/OCC, $R_A$ or $R_v$ and true $k_3/k_4$, although the slopes between them were not unity. Pharmacokinetic computer simulations may be a very useful technique in studying dopamine transporter systems.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.