• Imaging Science in Dentistry
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• 제44권4호
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• pp.301-305
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• 2014

Purpose: The purpose of this study was to compare the accuracy of postoperative maxillary cyst (POMC) diagnosis by panoramic radiographs versus computed tomography (CT) and by oral and maxillofacial radiologists versus non-specialists. Materials and Methods: Sixty-five maxillary sinuses with POMCs and 63 without any lesion were assessed using panoramic radiographs and CT images by five oral and maxillofacial radiologists and five non-specialists on a five-point scale. The areas under receiver operating characteristic (ROC) curves were analyzed to determine the differences in diagnostic accuracy between the two imaging modalities and between the two groups of observers. The intra-observer agreement was determined, too. Results: The diagnostic accuracy of CT images was higher than that of panoramic radiographs in both groups of observers (p<0.05). The diagnostic accuracy of oral and maxillofacial radiologists for each method was higher than that of non-specialists (p<0.05). Conclusion: The use of CT improves the diagnosis of POMC, and radiological training and experience leads to more accurate evaluation.

• 대한방사선기술학회지:방사선기술과학
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• 제23권1호
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• pp.63-76
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• 2000

License system of radiologic technologists has been started since 1965 in Korea. This study is to explore directions on radiotechnologists' license system classified by subspecialty. For this purpose, the authors surveyed on radiotechnologists' license system classified by subspecialty, with the subject related to radiotechnologic societies. Additionally, data on qualification and license system associated with medical and health care field were collected. The results are as follows. 1. The main body for subspecialty system for radiologic technologists should be the Korea Radiologic Technologists Association and the Association should maintain a close cooperation with radiotechnologic societies. 2. A radiologic technologist should be a basic role once they pass the license examination. In addition, they can get a special qualification by subspecialty in radiologic technology. 3. Radiotechnologists' license system classified by subspecialty will be keep priorities in order and done systematically. Execution order is as follows ; This study proposes that radiotechnologists responsible for ultrasonography, computed tomography(CT), magnetic resonance imaging(MRI) and security management be started for the first stage. For the second stage, radiotechnologists for mammography, angio-cardiography, digital imaging, maxillo-facial and dental radiography, nuclear medicine, radio-therapeutic field should be in force. 4. Professional education course(basic and intensive) and clinical training program have to be made for the eligibility of radiotechnologists' license system classified by subspecialty. 5. Eligibility system of radiotechnologists' license system classified by subspecialty(non-government or government) has to be made. Further more, inquiry commission to investigate eligibility for radiotechnologists' license system should be established.

• 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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• 제52권4호
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• pp.383-391
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• 2022

Purpose: Periodontitis, the most prevalent chronic inflammatory condition affecting teeth-supporting tissues, is diagnosed and classified through clinical and radiographic examinations. The staging of periodontitis using panoramic radiographs provides information for designing computer-assisted diagnostic systems. Performing image segmentation in periodontitis is required for image processing in diagnostic applications. This study evaluated image segmentation for periodontitis staging based on deep learning approaches. Materials and Methods: Multi-Label U-Net and Mask R-CNN models were compared for image segmentation to detect periodontitis using 100 digital panoramic radiographs. Normal conditions and 4 stages of periodontitis were annotated on these panoramic radiographs. A total of 1100 original and augmented images were then randomly divided into a training (75%) dataset to produce segmentation models and a testing (25%) dataset to determine the evaluation metrics of the segmentation models. Results: The performance of the segmentation models against the radiographic diagnosis of periodontitis conducted by a dentist was described by evaluation metrics(i.e., dice coefficient and intersection-over-union [IoU] score). MultiLabel U-Net achieved a dice coefficient of 0.96 and an IoU score of 0.97. Meanwhile, Mask R-CNN attained a dice coefficient of 0.87 and an IoU score of 0.74. U-Net showed the characteristic of semantic segmentation, and Mask R-CNN performed instance segmentation with accuracy, precision, recall, and F1-score values of 95%, 85.6%, 88.2%, and 86.6%, respectively. Conclusion: Multi-Label U-Net produced superior image segmentation to that of Mask R-CNN. The authors recommend integrating it with other techniques to develop hybrid models for automatic periodontitis detection.

• Imaging Science in Dentistry
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• 제52권4호
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• pp.351-357
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• 2022

Purpose: Convolutional neural networks (CNNs) have rapidly emerged as one of the most promising artificial intelligence methods in the field of medical and dental research. CNNs can provide an effective diagnostic methodology allowing for the detection of early-staged diseases. Therefore, this study aimed to evaluate the performance of a deep CNN algorithm for apical lesion segmentation from panoramic radiographs. Materials and Methods: A total of 1000 panoramic images showing apical lesions were separated into training (n=800, 80%), validation (n=100, 10%), and test (n=100, 10%) datasets. The performance of identifying apical lesions was evaluated by calculating the precision, recall, and F1-score. Results: In the test group of 180 apical lesions, 147 lesions were segmented from panoramic radiographs with an intersection over union (IoU) threshold of 0.3. The F1-score values, as a measure of performance, were 0.828, 0.815, and 0.742, respectively, with IoU thresholds of 0.3, 0.4, and 0.5. Conclusion: This study showed the potential utility of a deep learning-guided approach for the segmentation of apical lesions. The deep CNN algorithm using U-Net demonstrated considerably high performance in detecting apical lesions.

• 한국방사선학회논문지
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• 제17권3호
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• pp.459-464
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• 2023

첨단 기술의 발전으로 디지털 방사선영상 장비들이 많이 개발되어 정확한 진단과 치료에 많은 도움을 받고 있으며, 이를 안전하고 효과적으로 사용하기 위하여 전문적인 지식을 습득한 인력양성이 매우 중요하다. 진단용 X선 장비를 활용한 촬영 실습 교육에 있어서 학생들은 방사선 피폭의 위험성에 노출되어 있고, 일부 교육기관에서는 원자력안전법에 따른 관리의 어려움으로 X선 장비를 사용하지 않는 경우도 발생하고 있다. 이에 대한 해결책으로, 본 연구에서는 비전 센서와 자체 개발한 소프트웨어를 활용하여 방사선이 발생하지 않는 교육용 의료방사선 시뮬레이터를 개발하였고, 이를 통해 교육기관은 법에 따른 행정 이행 사항의 부담을 줄일 수 있고, 학생들은 방사선 피폭이 없는 건강한 실습환경에서 높은 수준의 교육 효과를 얻을 수 있게 하였다.

• 한국임상수의학회지
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• 제40권3호
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• pp.215-220
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• 2023

A 3-month-old Korean native cattle (Hanwoo) calf with difficulty taking normal posture and an inability to rise was referred for a definite diagnosis and active treatment, including surgery. The calf had a history of an accident in which both hind limbs were trapped in a barn structure. After admission, a "rabbit leg" posture was observed, a typical sign of gastrocnemius muscle rupture, and both digits were knuckled downward like they were trying to grip the ground. This was considered to be a result of the superficial digital flexor not rupturing but only the gastrocnemius muscle rupturing. Physical examination revealed laceration of the metatarsus and firmness behind both stifle joints which were presumed to be the sites of gastrocnemius muscle rupture. Skeletal abnormalities, including fractures, were ruled out by radiography. Based on these findings, the patient was diagnosed with bilateral gastrocnemius muscle rupture, and surgery was performed to reconnect the head of the ruptured muscle. Because the rupture occurred perpendicular to the muscle direction, the locking loop technique, a method of suturing severed tendons, was used to reduce the tension. After surgery, the cast was used to prevent further injuries and promote voluntary rehabilitation. Follow-up was completed, with the calf showing normal posture and gait 112 days after surgery. This is the first case report in the Republic of Korea describing the successful diagnosis and treatment of bilateral gastrocnemius muscle rupture in a calf.

• 치위생과학회지
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• 제23권4호
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• pp.343-350
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• 2023

Background: Digital panoramic dental X-ray equipment (PDX) is frequently used by patients and dental workers for diagnosis and examination in dental institutions; however, infection control has not been properly implemented. Therefore, in this study, we aimed to systematically review the potential risk of cross-infection in the dental environment by investigating the contamination level of general aerobic bacteria and Staphylococcus aureus, which are important in hospital infections, in PDX areas that people mainly contact. Methods: This survey was conducted from March to May 2023 and covered one general hospital, three dental hospitals, and nine dental clinics equipped with PDX. Bacteria samples were collected from the left-handle, right-handle, forehead support, and head side support as the patient's contact areas, as well as the X-ray exposure switch and left-click mouse button as the dental hygienist's contact areas of the PDX. The collected bacteria were spread on Petrifilm, and colonies formed after 48 hours of culture were counted. Results: General aerobic bacteria and S. aureus were detected in all areas investigated. Significant differences in bacterial counts between different regions of the PDX were observed in both groups (p<0.001). The detection rates of general aerobic bacteria (p<0.001) and S. aureus (p<0.001) were significantly higher in the contact areas of patients than those of dental hygienists. A positive correlation was observed between the forehead and the temple region in terms of general aerobic bacteria and S. aureus detection (r=1) (p<0.01). Conclusion: Taken together, the presence of many bacteria, including S. aureus, detected in PDX indicates that PDX has a potential cross-infection risk. Our results therefore highlight the need for the development of appropriate disinfection protocols for reusable medical devices such as PDX and periodic infection prevention training for hospital-related workers, including dental hygienists.

• International Journal of Computer Science & Network Security
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• 제24권5호
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• pp.53-63
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• 2024

Alzheimer's disease is a brain disorder that worsens over time and affects millions of people around the world. It leads to a gradual deterioration in memory, thinking ability, and behavioral and social skills until the person loses his ability to adapt to society. Technological progress in medical imaging and the use of artificial intelligence, has provided the possibility of detecting Alzheimer's disease through medical images such as magnetic resonance imaging (MRI). However, Deep learning algorithms, especially convolutional neural networks (CNNs), have shown great success in analyzing medical images for disease diagnosis and classification. Where CNNs can recognize patterns and objects from images, which makes them ideally suited for this study. In this paper, we proposed to compare the performances of Alzheimer's disease detection by using two deep learning methods: You Only Look Once (YOLO), a CNN-enabled object recognition algorithm, and Visual Geometry Group (VGG16) which is a type of deep convolutional neural network primarily used for image classification. We will compare our results using these modern models Instead of using CNN only like the previous research. In addition, the results showed different levels of accuracy for the various versions of YOLO and the VGG16 model. YOLO v5 reached 56.4% accuracy at 50 epochs and 61.5% accuracy at 100 epochs. YOLO v8, which is for classification, reached 84% accuracy overall at 100 epochs. YOLO v9, which is for object detection overall accuracy of 84.6%. The VGG16 model reached 99% accuracy for training after 25 epochs but only 78% accuracy for testing. Hence, the best model overall is YOLO v9, with the highest overall accuracy of 86.1%.

• 한국방사선학회논문지
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• 제6권5호
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• pp.421-426
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• 2012

본 연구의 목적은 치위생 전공 학생들의 치과방사선 장비 및 물품의 질관리에 관한 지식수준을 파악하고, 방사선 질관리에 대한 이론 및 실습 교육정도를 조사하여 치과위생사 양성과정에서의 체계적인 방사선 질관리와 관련된 교육과정 개설 및 개편을 위해 필요한 기초자료를 제공하고자 한다. 연구의 목적을 달성하기 위해서 치위생 전공 학생 중 치과방사선 과목을 수강한 학생 453명을 대상으로 설문조사를 실시하였다. 분석 가능한 자료를 SPSS 12.0을 활용하여 자료를 분석하였으며, 연구대상자의 변인별 특성을 알아보기 위해 빈도분석, 신뢰도분석, 카이제곱 검정, 독립 T-test, 일원배치분산분석 후 사후검정으로 scheffe 방법을 실시하였다. 분석결과, 첫째, 방사선 질관리에 대한 지식수준은 12점 만점 중 평균 $7.71{\pm}1.7$점으로 나타났으며 치과방사선 교과목 이수 시 이론수업과 실습수업을 받을수록, 지식수준이 높게 나타났다(p<0.001). 둘째, 방사선 질관리에 대한 임상실습교육 수준은 13개 항목 중 1~3개를 경험한 학생수가 가장 많은 것으로 나타났으며, 임상실습교육을 전혀 받지 않은 학생도 26.3%로 조사되어 방사선 질관리에 관한 적절한 실습교육을 위탁교육기관에서 제공해야 할 필요성이 있었다. 셋째, 방사선 질관리에 대한 실습교육 13개 항목중 질관리 실습을 전혀 경험하지 못한 사람의 정답 문항 수는 평균 7.20개, 1~3개 항목을 교육받은 사람의 정답 문항수는 평균 7.84개, 4~5개 항목을 교육받은 사람의 정답 문항수는 평균 7.87개, 6개 이상 항목을 교육받은 사람의 정답 문항수는 8.14개로 나타났으며, 임상실습교육기간 중 질관리 관련 교육 경험수가 많을수록 지식수준이 높은 것으로 나타났다.