• Journal of the Korean Society of Radiology
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• v.17 no.4
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• pp.557-564
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• 2023

In this study, 3D printing technology was used to compensate for the shortcomings of the use of lead, which has proven to have excellent shielding performance, and to control unnecessary human exposure. 3D printers can implement three-dimensional shapes and can immediately apply individual ideas, which has great advantages in maintaining technology supplementation while reducing the cost and duration of prototyping. Among the various special 3D printers, the FDM method was adopted, and the filament used for output was manufactured using a research extruder by mixing two materials, PLA (Poly-Lactic-Acid) and tungsten. The purpose was to verify the validity through dose evaluation and to provide basic information on the production of chapezones of various materials. The mixed filament was implemented as a morphological shield. Filaments made of a research extruder by mixing PLA and tungsten were divided into 10 %, 20 %, 30 %, 40 %, and 50 % according to the tungsten content ratio. Through the process of 3D Modeling, STL File storage, G-code generation, and output, 10 cm × 10 cm × 0.5 cm was manufactured, respectively, and dose and shielding ability were evaluated under the conditions of tube voltages of 60 kVp, 80 kVp, 100 kVp, 120 kVp, and tube currents of 20 mAs and 40 mAs.

• Journal of radiological science and technology
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• v.47 no.5
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• pp.367-374
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• 2024

Education on start-ups and social support through various programs can greatly assist students who are either planning to start a business or have future entrepreneurial aspirations. This study aims to examine the impact of entrepreneurship education, social support, and awareness of the intend to start a business for students enrolled in radiological science program at local universities. The reliability of the questionnaire tool was confirmed with a Cronbach's Alpha coefficient of .06 or higher in the variable. The result of the independent sample t-test using the Boot Strap technique was classified by gender, revealed significant differences in the intention to start a business and innovation. The Bias-Corrected and Accelerated (BCa) 95% confidence interval for the intention to start a business and innovation was lower at .268 and .100, respectively, and the upper limit was .825 and .457, indicating a significant difference as the interval did not include zero. As a result of regression analysis, analysis demonstrated that among the sub-factors of entrepreneurship, innovation (p<.05) and risk sensitivity (p<.001) significantly influenced the willingness to start a business. These findings suggest that comprehensive education on start-ups, along with the provision of appropriate support mechanisms, is essential to ensure the students do not miss out on entrepreneurial opportunities due to a lack of related resources and support.

• Imaging Science in Dentistry
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• v.46 no.4
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• pp.229-237
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• 2016

Purpose: The aim of this article is to review a group of lesions associated with periodontal ligament (PDL) widening. Materials and Methods: An electronic search was performed using specialized databases such as Google Scholar, PubMed, PubMed Central, Science Direct, and Scopus to find relevant studies by using keywords such as "periodontium", "periodontal ligament", "periodontal ligament space", "widened periodontal ligament", and "periodontal ligament widening". Results: Out of nearly 200 articles, about 60 were broadly relevant to the topic. Ultimately, 47 articles closely related to the topic of interest were reviewed. When the relevant data were compiled, the following 10 entities were identified: occlusal/orthodontic trauma, periodontal disease/periodontitis, pulpo-periapical lesions, osteosarcoma, chondrosarcoma, non-Hodgkin lymphoma, progressive systemic sclerosis, radiation-induced bone defect, bisphosphonate-related osteonecrosis, and osteomyelitis. Conclusion: Although PDL widening may be encountered by many dentists during their routine daily procedures, the clinician should consider some serious related conditions as well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2627-2647
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• 2016

With the rapid growth of microblog, expert identification on microblog has been playing a crucial role in many applications. While most previous expert identification studies only assess global authoritativeness of a user, there is no way to differentiate the authoritativeness in a particular aspect of topics. In this paper, we propose a novel model, which jointly models text and following relationship in the same generative process. Furthermore, we integrate a similarity-based weight scheme into the model to address the popular bias problem, and use followee topic distribution as prior information to make user's topic distribution more precisely. Our empirical study on two large real-world datasets shows that our proposed model produces significantly higher quality results than the prior arts.

• International Journal of Contents
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• v.17 no.1
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• pp.18-26
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• 2021

The obesity leads to be the result of the weakening of anatomical structure as well as the gravity effect. And, the obesity interferes with normal sagittal balance and fails to maintain a straight posture with minimal energy. Therefore, the obesity can be an important factor in causing back pain by changing the lumbar lordosis. In this study, we will present an appropriate angle of incidence for obese people to reduce the image distortion of L4, L5 during a general anteroposterior radiography examination. To reduce image distortion according to the change of lordosis, the angle of incidence was applied 9 ° and 21 ° to L4 and L5 vertebra body when obesity and low back pain (LBP) perform the general anteroposterior radiography examination.

• Journal of Digestive Cancer Research
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• v.11 no.3
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• pp.157-164
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• 2023

Prediction is a significant topic in clinical research. The development and validation of a prediction model has been increasingly published in clinical research. In this review, we investigated analytical methods and validation schemes for a clinical prediction model used in digestive cancer research. Deep learning and logistic regression, with split-sample validation as an internal or external validation, were the most commonly used methods. Furthermore, we briefly introduced and summarized the advantages and disadvantages of each method. Finally, we discussed several points to consider when conducting prediction model studies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.5860-5866
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• 2012

BOLD technique in functional MRI has to apply multiple stimulations. However as the stimulation time increases failure rates rise. In this study we are proposing proper number of stimulations through our experiments. Ten normal people underwent functional MRI hand motor sanning and the paradigms were designed from first to seventh stimulation. Under Philips Intera Achieva 3.0T MR system and Invivo cop's Eloquence equipment, activation periods and rest periods were repeated ten times each, using BOLD EPI technique. Primary hand motor area stimulation and number of clusters, activation rates and number of activated clusters in and outside the region of interest were compared to each other. Number of clusters in region of interest was lower than others at second stimulation and became static from third stimulation. The stimulated ratios were elevated as the number of stimulations were increased but it was not proportional. Number of clusters outside the ROI became static from the third stimulation and started increasing from sixth stimulation. As results, given the activation ratios of ROI and out side the ROI, three times stimulation was the most appropriate because it does not affect accuracy, also decreasing the fatigue of patients by with the decreased scanning time.

• Journal of the Korean Society of Radiology
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• v.17 no.1
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• pp.25-30
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• 2023

As 3D printing technology is used in the medical field, interest in metal materials is increasing. The Department of Radiation Oncology uses a shielding block to shield the patient's normal tissue from unnecessary exposure during electron beam therapy. However, problems such as handling of heavy metal materials such as lead and cadmium, reproducibility according to skill level and uncertainty of arrangement have been reported. In this study, candidate materials that can be used for metal 3D printing are selected, and the physical properties and radiation dose of each material are analyzed to develop a customized shielding block that can be used in electron beam therapy. As candidate materials, aluminum alloy (d = 2.68 g/cm³), titanium alloy (d = 4.42 g/cm³), and cobalt chromium alloy (d = 8.3 g/cm³) were selected. The thickness of the 95% shielding rate point was derived using the Monte Carlo Simulation with the irradiation surface and 6, 9, 12, and 16 energies. As a result of the simulation, among the metal 3D printing materials, cobalt chromium alloy (d = 8.3 g/cm³) was similar to the existing shielding block (d = 9.4 g/cm³) in shielding thickness for each energy. In a follow-on study, it is necessary to evaluate the usefulness in clinical practice using customized shielding blocks made by metal 3D printing and to verify experiments through various radiation treatment plan conditions.

• Journal of radiological science and technology
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• v.47 no.1
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• pp.39-48
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• 2024

In this study, we optimized the FNLM algorithm through a simulation study and applied it to a phantom scanned by low-dose CT to evaluate whether the FNLM algorithm can be used to obtain improved image quality images. We optimized the FNLM algorithm with MASH phantom and FASH phantom, which the algorithm was applied with MATLAB, increasing the smoothing factor from 0.01 to 0.05 with increments of 0.001 and measuring COV, RMSE, and PSNR values of the phantoms. For both phantom, COV and RMSE decreased, and PSNR increased as the smoothing factor increased. Based on the above results, we optimized a smoothing factor value of 0.043 for the FNLM algorithm. Then we applied the optimized FNLM algorithm to low dose lung CT and lung CT under normal conditions. In both images, the COV decreased by 55.33 times and 5.08 times respectively, and we confirmed that the quality of the image of low dose CT applying the optimized FNLM algorithm was 5.08 times better than the image of lung CT under normal conditions. In conclusion, we found that the smoothing factor of 0.043 among the factors of the FNLM algorithm showed the best results and validated the performance by reducing the noise in the low-quality CT images due to low dose with the optimized FNLM algorithm.

• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.1-5
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• 2021

Although CT has an advantage in describing the three-dimensional anatomical structure of the human body, it also has a disadvantage in that high doses are exposed to the patient. Recently, a deep learning-based image reconstruction method has been used to reduce patient dose. The purpose of this study is to analyze the dose reduction and image quality improvement of deep learning-based reconstruction (DLR) on the adult's chest CT examination. Adult lung phantom was used for image acquisition and analysis. Lung phantom was scanned at ultra-low-dose (ULD), low-dose (LD), and standard dose (SD) modes, and images were reconstructed using FBP (Filtered back projection), IR (Iterative reconstruction), DLR (Deep learning reconstruction) algorithms. Image quality variations with respect to varying imaging doses were evaluated using noise and SNR. At ULD mode, the noise of the DLR image was reduced by 62.42% compared to the FBP image, and at SD mode, the SNR of the DLR image was increased by 159.60% compared to the SNR of the FBP image. Based on this study, it is anticipated that the DLR will not only substantially reduce the chest CT dose but also drastic improvement of the image quality.