• Imaging Science in Dentistry
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• 제52권2호
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• pp.141-153
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• 2022

Purpose: This study aimed to identify the prevalence and extension of the anterior loop (AL) of the mental nerve in different populations and according to different cone-beam computed tomography (CBCT) imaging settings. Materials and Methods: Medline/PubMed, Embase, Scopus, Web of Science, and ProQuest were searched. The main inclusion criterion was ALs evaluated in CBCT images. The quality of studies was assessed with the Joanna Briggs Institute risk of bias checklist. Subgroup analyses were conducted for sex, side, continent, voxel size, field of view, and type of CBCT-reconstruction images with a random-effects model. Results: Sixty-three studies with 13,743 participants (27,075 hemimandibles) were included. An AL was found in 40.6% (95% CI: 32.8%-48.9%, P<0.05) of participants and 36.0% (95% CI: 27.5%-45.5%, P<0.05) of hemimandibles, in 34.9% (95% CI: 25.1%-46.2%, P<0.05) of males and 34.5% (95% CI: 23.5%-47.4%, P<0.05) of females. The average length of ALs was 2.39 mm (95% CI: 2.07-2.70 mm, P<0.05). Their extension was 2.13 mm (95% CI: 1.54-2.73 mm, P<0.05) in males and 1.85 mm (95% CI: 1.35-2.36 mm, P<0.05) in females. Significant differences were observed regarding the prevalence and length of ALs among continents and for its measured length on different CBCT-reconstruction images, but not between other subgroups. Conclusion: AL was a relatively common finding. The voxel size and fields of view of CBCT devices were adequate for assessing AL; however, a 2-mm safety margin from anatomical structures(such as the AL) could be recommended to be considered when using CBCT imaging.

• Imaging Science in Dentistry
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• 제52권3호
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• pp.239-244
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• 2022

Purpose: Despite the proliferation of numerous morphometric and anthropometric methods for sex identification based on linear, angular, and regional measurements of various parts of the body, these methods are subject to error due to the observer's knowledge and expertise. This study aimed to explore the possibility of automated sex determination using convolutional neural networks(CNNs) based on lateral cephalometric radiographs. Materials and Methods: Lateral cephalometric radiographs of 1,476 Iranian subjects (794 women and 682 men) from 18 to 49 years of age were included. Lateral cephalometric radiographs were considered as a network input and output layer including 2 classes(male and female). Eighty percent of the data was used as a training set and the rest as a test set. Hyperparameter tuning of each network was done after preprocessing and data augmentation steps. The predictive performance of different architectures (DenseNet, ResNet, and VGG) was evaluated based on their accuracy in test sets. Results: The CNN based on the DenseNet121 architecture, with an overall accuracy of 90%, had the best predictive power in sex determination. The prediction accuracy of this model was almost equal for men and women. Furthermore, with all architectures, the use of transfer learning improved predictive performance. Conclusion: The results confirmed that a CNN could predict a person's sex with high accuracy. This prediction was independent of human bias because feature extraction was done automatically. However, for more accurate sex determination on a wider scale, further studies with larger sample sizes are desirable.

• Imaging Science in Dentistry
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• 제52권3호
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• pp.283-288
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• 2022

Purpose: This study was conducted to measure the radiation exposure and image quality of various cone-beam computed tomography (CBCT) machines under common clinical conditions and to analyze the correlation between them. Materials and Methods: Seven CBCT machines used frequently in clinical practice were selected. Because each machine has various sizes of fields of view (FOVs), 1 large FOV and 1 small FOV were selected for each machine. Radiation exposure was measured using a dose-area product (DAP) meter. The quality of the CBCT images was analyzed using 8 image quality parameters obtained using a dental volume tomography phantom. For statistical analysis, regression analysis using a generalized linear model was used. Results: Polymethyl-methacrylate (PMMA) noise and modulation transfer function (MTF) 10% showed statistically significant correlations with DAP values, presenting positive and negative correlations, respectively (P<0.05). Image quality parameters other than PMMA noise and MTF 10% did not demonstrate statistically significant correlations with DAP values. Conclusion: As radiation exposure and image quality are not proportionally related in clinically used equipment, it is necessary to evaluate and monitor radiation exposure and image quality separately.

• Imaging Science in Dentistry
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• 제52권4호
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• pp.399-408
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• 2022

Purpose: The purpose of this study was to compare volume measurements obtained using 2 image software packages on Digital Imaging and Communications in Medicine (DICOM) images acquired from 1 multidetector computed tomography and 5 cone-beam computed tomography devices, using different protocols for physical volume measurements. Materials and Methods: Four pieces of bovine leg were prepared. Marrow was removed from 3 pieces, leaving cortical bone exposed. The resulting space of 1 piece was filled with water, another was filled with propylene glycol, and the third was left unfilled. The marrow in the fourth sample was left fully intact. Volume measurements were obtained after importing DICOM images into the Dolphin Imaging 11.95 and ITK-SNAP software programs. Data were analyzed using 3-way analysis of variance with a generalized linear model to determine the effects of voxel size, software, and content on percentage mean volume differences between tomographic protocols. A significance level of 0.05 was used. Results: The intraclass correlation coefficients for intraobserver and interobserver reliability were, respectively, 0.915 and 0.764 for the Dolphin software and 0.894 and 0.766 for the ITK-SNAP software. Three sources of statistically significant variation were identified: the interaction between software and content (P=0.001), the main effect of content (P=0.014), and the main effect of software (P=0.001). Voxel size was not associated with statistically significant differences in volume measurements. Conclusion: Both content and software influenced the accuracy of volume measurements, especially when the content had gray values similar to those of the adjacent tissues.

• Korean Journal of Acupuncture
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• 제39권4호
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• pp.184-190
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• 2022

Objectives : In our previous study, we developed the prototype of a lesson plan for meridian and acupuncture clinical skills education by applying the rapid prototyping to instructional systems design. The present study aimed to develop a teaching-learning manual, including the lesson plans, practice notes, and instructions for devices. We also aimed to present a guideline on how to use the manual in class. Methods : The manual and materials for teachers and learners were developed based on the solutions and the prototype derived from our previous study. Practical classes on meridian and acupuncture points consist of four major subjects, and the lesson plan and practice note were designed according to each topic. Results : Flipped learning, George's five-step method, peer role-play, and peer-led objective structured clinical examination (OSCE) were applied as main methodologies in the meridian and acupuncture points practical class. The teaching-learning manual, including practice notes, detailed lesson plan, OSCE checklist, and instruction manual for devices, was developed to be utilized at each stage of the learning activity. Conclusions : The application of the teaching-learning manual is expected to provide effective clinical skills education, strengthen learners' communication skills, establish professional identity, assess learners' performance, and provide immediate feedback. The educational effect of the manual for the existing class should be identified, and its feasibility should be verified by implementing it on another group. This manual could be helpful in designing classes for other subjects of Korean medicine, especially for clinical skills education.

• Imaging Science in Dentistry
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• 제53권3호
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• pp.221-227
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• 2023

Purpose: This study was performed to develop a linear regression model using the pulp-to-tooth volume ratio (PTVR) ratio of the maxillary canine, assessed through cone-beam computed tomography (CBCT) images, to predict chronological age (CA) in Indonesian adults. Materials and Methods: A sample of 99 maxillary canines was collected from patients between 20 and 49.99 years old. These samples were obtained from CBCT scans taken at the Universitas Padjadjaran Dental Hospital in Indonesia between 2018 and 2022. Pulp volume (PV) and tooth volume (TV) were measured using ITK-SNAP, while PTVR was calculated from the PV/TV ratio. Using RStudio, a linear regression was performed to predict CA using PTVR. Additionally, correlation and observer agreement were assessed. Results: The PTVR method demonstrated excellent reproducibility, and a significant correlation was found between the PTVR of the maxillary canine and CA(r= -0.74, P<0.01). The linear regression analysis showed an R² of 0.58, a root mean square error of 5.85, and a mean absolute error of 4.31. Conclusion: Linear regression using the PTVR can be effectively applied to predict CA in Indonesian adults between 20 and 49.99 years of age. As models of this type can be population-specific, recalibration for each population is encouraged. Additionally, future research should explore the use of other teeth, such as molars.

• Imaging Science in Dentistry
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• 제53권4호
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• pp.271-281
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• 2023

Purpose: The objective of this scoping review was to investigate the applicability and performance of various convolutional neural network (CNN) models in tooth numbering on panoramic radiographs, achieved through classification, detection, and segmentation tasks. Materials and Methods: An online search was performed of the PubMed, Science Direct, and Scopus databases. Based on the selection process, 12 studies were included in this review. Results: Eleven studies utilized a CNN model for detection tasks, 5 for classification tasks, and 3 for segmentation tasks in the context of tooth numbering on panoramic radiographs. Most of these studies revealed high performance of various CNN models in automating tooth numbering. However, several studies also highlighted limitations of CNNs, such as the presence of false positives and false negatives in identifying decayed teeth, teeth with crown prosthetics, teeth adjacent to edentulous areas, dental implants, root remnants, wisdom teeth, and root canal-treated teeth. These limitations can be overcome by ensuring both the quality and quantity of datasets, as well as optimizing the CNN architecture. Conclusion: CNNs have demonstrated high performance in automated tooth numbering on panoramic radiographs. Future development of CNN-based models for this purpose should also consider different stages of dentition, such as the primary and mixed dentition stages, as well as the presence of various tooth conditions. Ultimately, an optimized CNN architecture can serve as the foundation for an automated tooth numbering system and for further artificial intelligence research on panoramic radiographs for a variety of purposes.

• Imaging Science in Dentistry
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• 제54권2호
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• pp.159-169
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• 2024

Purpose: The aim of this study was to evaluate the influence of different cone-beam computed tomography (CBCT) acquisition protocols on reducing the effective radiation dose while maintaining image quality. Materials and Methods: The effective dose emitted by a CBCT device was calculated using thermoluminescent dosimeters placed in a Rando Alderson phantom. Image quality was assessed by 3 experienced evaluators. The relationship between image quality and confidence was evaluated using the Fisher exact test, and the agreement among raters was assessed using the kappa test. Multiple linear regression analysis was performed to investigate whether the technical parameters could predict the effective dose. P-values<0.05 were considered to indicate statistical significance. Results: The optimized protocol (3 mA, 99 kVp, and 450 projection images) demonstrated good image quality and a lower effective dose for radiation-sensitive organs. Image quality and confidence had consistent values for all structures (P<0.05). Multiple linear regression analysis resulted in a statistically significant model. The milliamperage (b=0.504; t=3.406; P=0.027), kilovoltage peak (b=0.589; t=3.979; P=0.016) and number of projection images (b=0.557; t=3.762; P=0.020) were predictors of the effective dose. Conclusion: Optimized CBCT acquisition protocols can significantly reduce the effective radiation dose while maintaining acceptable image quality by adjusting the milliamperage and projection images.

• Imaging Science in Dentistry
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• 제54권3호
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• pp.257-263
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• 2024

Purpose: The purpose of this study was to classify mandibular molar furcation involvement (FI) in periapical radiographs using a deep learning algorithm. Materials and Methods: Full mouth series taken at East Carolina University School of Dental Medicine from 2011-2023 were screened. Diagnostic-quality mandibular premolar and molar periapical radiographs with healthy or FI mandibular molars were included. The radiographs were cropped into individual molar images, annotated as "healthy" or "FI," and divided into training, validation, and testing datasets. The images were preprocessed by PyTorch transformations. ResNet-18, a convolutional neural network model, was refined using the PyTorch deep learning framework for the specific imaging classification task. CrossEntropyLoss and the AdamW optimizer were employed for loss function training and optimizing the learning rate, respectively. The images were loaded by PyTorch DataLoader for efficiency. The performance of ResNet-18 algorithm was evaluated with multiple metrics, including training and validation losses, confusion matrix, accuracy, sensitivity, specificity, the receiver operating characteristic (ROC) curve, and the area under the ROC curve. Results: After adequate training, ResNet-18 classified healthy vs. FI molars in the testing set with an accuracy of 96.47%, indicating its suitability for image classification. Conclusion: The deep learning algorithm developed in this study was shown to be promising for classifying mandibular molar FI. It could serve as a valuable supplemental tool for detecting and managing periodontal diseases.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2002년도 춘계학술대회 논문집
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• pp.417-424
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• 2002

컴퓨터는 인간의 모든 꿈과 희망을 실현시켜 줄 수 있는 마법상자는 아니다. 정보화 시대라고 일컫는 현재, 정보의 가치를 더해주는 컴퓨터의 중요성은 날로 커지고 있는 반면 인간의 존엄성은 경시되고 있다. 많은 사람들은 요즘 사회가 커다란 도덕적 위기에 빠졌다고 걱정하지만 컴퓨터 사용과 관련된 윤리적 문제에 대해서는 심각하게 느끼지 못하고 있는 것 같다. 정보통신 기술의 발달에 따라 새로운 교육의 필요성이 대두되고 있다. 기존의 전통적인 교육방식에서 사이버 윤리 교육은 교과서 중심의 단편적인 교육이었기 때문에 학습자의 흥미를 유발하지 못하였으며, 교육자와 학습자의 상호작용이 부족하여 사이버 윤리 교육의 효과가 미흡하였다. 정보통신 기술의 발달에 따라 새로운 교육의 필요성이 대두되고 있다. 기존의 전통적인 교육방식에서 사이버 윤리 교육은 교과서 중심의 단편적인 교육이었기 때문에 학습자의 흥미를 유발하지 못하였으며, 교육자와 학습자의 상호작용이 부족하여 사이버 윤리 교육의 효과가 미흡하였다. 이런 관점에서 본 논문은 정보통신 시대가 수반하고 있는 사회적 영향력과 윤리적 이슈들에 대하여 좀더 교육적인 측면으로 접근해 윤리교육의 현황과 문제점, 그리고 체계적인 확산방안에 대해 살펴보았다. 본 논문에서는 사이버공간에서 윤리 교육을 받는 청소년들을 중심으로 그들에게 새로운 윤리교육의 한 형태인 사이버공간에서 관련된 문제들을 교육적인 측면으로 해결할 수 있는 방안을 제시하고자 한다. 그러나, 무엇보다 우리가 명심해야 할 것은 인간의 존엄성은 그 어떤 이유를 막론하고 존중되어야 한다는 사실이다. 검증되지 않은 스토리 보드에 의한 저작 단계로 바로 돌입하고 있는 것이 한국의 실정이라 하겠다. 따라서 본 프로젝트에 의해 개발 된 교수 설계 도구는 교육/학습 컨텐츠의 품질 보증을 위한 방법론인 교육 공학의 체제적 교수 설계 이론 Model (Instructional System Design Model), 특히 그 중에서도 이 분야의 사실상의 표준 이론(de facto standard)인 Dick & Carey 교수와 Gagne 교수의 인지주의 ISD Model을 기반으로 정교한 교수 설계와 코스 맵 설계를 가능하게 함으로써 학습 컨텐츠의 품질 보증 활동을 지원 할 수 있는 도구로 개발하였다. 특히 Linux 기반에서 PHP로 개발 함으로써 Platform에 구애받지 않은 사용 환경을 구현 하였으며 향후 많은 e-Learning Platform에 교수 설계 모듈로 장착 함으로써 기존의 e-Learning Platform들의 가치를 높일 수 있는 계기가 될 것으로 생각한다.실징후를 파악하는데 그치지 않고 부실의 원인을 파악하고 이에 대한 대응 전략을 수립하며 그 결과를 측정하는데 활용될 수도 있다. 따라서 본 연구에서는 기업의 부도예측 정보 중 현금흐름정보를 통하여 '인터넷기업의 미래 현금흐름측정, 부도예측신호효과, 부실원인파악, 비즈니스 모델의 성격규정 등을 할 수 있는가'를 검증하려고 한다. 협력체계 확립, ${\circled}3$ 전문인력 확보 및 인력구성 조정, 그리고 ${\circled}4$ 방문보건사업의 강화 등이다., 대사(代謝)와 관계(