• Journal of Korean Foot and Ankle Society
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• v.9 no.1
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• pp.94-98
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• 2005

Purpose: To compare the radiographic evaluations between two radiographic views (AP and lateral views) and four radiographic views (AP, lateral and both oblique views) in ankle fractures. Materials and Methods: From January 2000 to June 2002, 60 cases of ankle fractures were treated with open reduction and internal fixation and its followed up periods were at least 2 years. All cases were classified into three groups according to the method of preoperative radiographic evaluation. Two radiographic views (AP and lateral views) were taken in group A and four radiographic views (AP, lateral and both oblique views) were taken in group B. 12 Cases were evaluated with three dimensional computed tomography (3D CT). Four radiographic views and 3D CT were taken in group C. All cases were classified according to the Danis-Weber and Lauge-Hansen classification. Displacement of fracture fragment of medial, lateral, posterior malleolus and size of fracture fragment of posterior malleous were measured using picture archiving communication system (PACS). Results: Although kappa value between two or four radiographic views were good or excellent in Danis-Weber classification and Lauge-Hansen classification of ankle fractures, the displacements of medial and lateral malleoli were statistically different. Four radiographic views evalulated the degree of displacement of medial and lateral fragments more accurately compared to two radiographic views. Conclusion: Four radiographic views will be more useful than two radiographic views to decide the method of treatment and operation considering the displacement of fracture fragment.

• Journal of Korean Foot and Ankle Society
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• v.11 no.2
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• pp.130-134
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• 2007

Purpose: To investigate the relationship between classification based on simple radiographic findings and arthroscopic findings of the cartilage lesions in medial degenerative arthritis of the ankle joint. Materials and Methods: We studied 41 ankles of 36 patients with asymmetrical narrowing of the medial joint space. Degenerative arthritis following fracture and those with generalized arthritic disease were excluded, but those with a history of ankle sprain were included. Standing radiographs of all patients were graded according to the Takakura classification and the Kellgren-Lawrence (K/L) classification. Arthroscopic findings were classified according to the depth, width, and anteroposterior dimension of articular cartilage damage. Results: According to the Takakura classification, 29 ankles were classified as stage II, 7 cases as stage IIIA and 2 cases as stage IIIB. According to our classification of arthroscopic findings of 29 ankles in stage II, 1 ankle was graded as Grade I, 3 ankles as grade II, 10 ankles as grade III, and 15 ankles as grade IV. Spearman correlation coefficient between Takakura classification and arthroscopic classification was 0.342 (P=0.028), and coefficient between K/L classification and arthroscopic classification was 0.480 (P=0.001). Conclusion: Degenerative changes of the articular cartilage are more advanced than radiographic findings in many patients with ankle degenerative arthritis with asymmetrical narrowing of medial joint space. Therefore, we conclude that more aggressive effort should be made for correct diagnosis and treatment of degenerative arthritis.

• Journal of Periodontal and Implant Science
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• v.53 no.1
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• pp.38-53
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• 2023

Purpose: The current Classification of Periodontal and Peri-Implant Diseases and Conditions, published and disseminated in 2018, involves some difficulties and causes diagnostic conflicts due to its criteria, especially for inexperienced clinicians. The aim of this study was to design a decision system based on machine learning algorithms by using clinical measurements and radiographic images in order to determine and facilitate the staging and grading of periodontitis. Methods: In the first part of this study, machine learning models were created using the Python programming language based on clinical data from 144 individuals who presented to the Department of Periodontology, Faculty of Dentistry, Süleyman Demirel University. In the second part, panoramic radiographic images were processed and classification was carried out with deep learning algorithms. Results: Using clinical data, the accuracy of staging with the tree algorithm reached 97.2%, while the random forest and k-nearest neighbor algorithms reached 98.6% accuracy. The best staging accuracy for processing panoramic radiographic images was provided by a hybrid network model algorithm combining the proposed ResNet50 architecture and the support vector machine algorithm. For this, the images were preprocessed, and high success was obtained, with a classification accuracy of 88.2% for staging. However, in general, it was observed that the radiographic images provided a low level of success, in terms of accuracy, for modeling the grading of periodontitis. Conclusions: The machine learning-based decision system presented herein can facilitate periodontal diagnoses despite its current limitations. Further studies are planned to optimize the algorithm and improve the results.

• Journal of Korean Foot and Ankle Society
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• v.5 no.1
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• pp.13-17
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• 2001

Objectives: This study was done to determine the prevalence of radiographic ankle osteoarthritis (OA) in Korean women with clinical primary ankle OA. Methods: This analysis involved 160 Korean women who visited our out patient clinic due to ankle joint pain. Ankle AP and lateral weight-bearing radiographs were evaluated retrospectively to check whether they have radiographic OA or not. Radiographs were read for features of ankle OA using School classification. Demographic factors and radiographic findings in both radiographic ankle OA group and non-radiographic ankle OA group were analyzed by the student t-test, the chi square test and the Pearson's analysis. A p value <0.05 was considered significant. Results: The prevalence of radiographic ankle OA in Korean women is 18.2 % in patient between 18 and 39 years and is 55.6 % in patient over 40. There was significant difference between two groups with age (P<0.001) and relatively strong correlation between radiographic OA and age (r=0.474, P<0.001). Conclusion: These results show that the prevalence of Korean women with radiographic changes of ankle OA was 45 % and there was relatively strong correlation between age and radiographic ankle OA.

• Imaging Science in Dentistry
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• v.32 no.3
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• pp.129-134
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• 2002

Purpose : To implement the database system of oral and maxillofacial radiological images using a commercial medical image management software with personally developed classification code. Materials and methods : The image database was built using a slightly modified commercial medical image management software, Dr. Image v.2.1 (Bit Computer Co., Korea). The function of wild card '*' was added to the search function of this program. Diagnosis classification codes were written as the number at the first three digits, and radiographic technique classification codes as the alphabet right after the diagnosis code. 449 radiological films of 218 cases from January, 2000 to December, 2000, which had been specially stored for the demonstration and education at Dept. of OMF Radiology of Dankook University Dental Hospital, were scanned with each patient information. Results: Cases could be efficiently accessed and analyzed by using the classification code. Search and statistics results were easily obtained according to sex, age, disease diagnosis and radiographic technique. Conclusion : Efficient image management was possible with this image database system. Application of this system to other departments or personal image management can be made possible by utilizing the appropriate classification code system.

• Journal of the korean academy of Pediatric Dentistry
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• v.51 no.1
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• pp.1-10
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• 2024

Deep learning algorithms are becoming more prevalent in dental research because they are utilized in everyday activities. However, dental researchers and clinicians find it challenging to interpret deep learning studies. This review aimed to provide an overview of the general concept of deep learning and current deep learning research in dental radiographic image analysis. In addition, the process of implementing deep learning research is described. Deep-learning-based algorithmic models perform well in classification, object detection, and segmentation tasks, making it possible to automatically diagnose oral lesions and anatomical structures. The deep learning model can enhance the decision-making process for researchers and clinicians. This review may be useful to dental researchers who are currently evaluating and assessing deep learning studies in the field of dentistry.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_2
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• pp.687-697
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• 2022

An automated system is needed for the effectiveness of non-destructive testing. In order to utilize the radiographic testing data accumulated in the film, the types of welding defects were classified into 9 and the shape of defects were analyzed. Data was preprocessed to use deep learning with high performance in image classification, and a combination of one-stage/two-stage method and convolutional neural networks/Transformer backbone was compared to confirm a model suitable for welding defect detection. The combination of two-stage, which can learn step-by-step, and deep-layered CNN backbone, showed the best performance with mean average precision 0.868.

• The Journal of the Korean dental association
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• v.57 no.12
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• pp.758-767
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• 2019

The classification of periodontal disease in 1999 has been widely used for determining a diagnosis, establishing a treatment plan, and evaluating the prognosis of the patient with periodontal disease. However, scientific evidence from many studies indicates the need for a new classification system for periodontal and peri-implant disease. Summary at 2017 world workshop as follows: 1) Periodontal health and peri-implant health was defined; 2) Chronic periodontitis and aggressive periodontitis were unified as periodontitis; 3) Periodontitis was further classified by staging and grading to reflect disease severity and management complexity, rate of disease progression, respectively; 4) Periodontal disease as manifestation of systemic disease is based on the International Statistical Classification of Diseases and Related Health Problems-10 (ICD-10) code; 5) Periodontal biotype and biologic width was replaced to periodontal phenotype and supracrestal tissue attachment, respectively; 6) The excessive occlusal force was replaced by a traumatic occlusal force; 7) ≥3 mm of radiographic bone loss, ≥6 mm of pocket probing depth and bleeding on probing indicates peri-implantitis in the absence of radiograph at final prosthesis delivery.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.10 no.1
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• pp.15-28
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• 1980

The author studied age and sex distribution, etiology, affected site and several radiographic features of osteomyelitis of the jaw. And radiologic classification of osteomyelitis was also done. The material consisted of 118 males and 96 females examined and/or treated under the diagnosis of osteomyelitis during past 11 years (1970-1980.6) in SNUDH. The obtained results were as followings. 1. The incidence is the highest in teenages(22.9%) and the lowest in seventies. (2.8%). 2. 199 cases were found in lower jaw, and 15 cases in upper jaw. 30.8% of all cases were located at the posterior portion of mandibular body comprising alveolar region. 3. Radiographic examination of osteolytic lesion revealed that 21. 5% of all patients had periapical and alveolar bone rarefaction combined with osteoporotic changes and that in most of patients two or more of the above described changes were present at the same time. 4. Sclerotic lesions were seen in 62.2 % of all patients and 21.5% of sclerotic lesion were diffuse or homogenuous type. 5. Based on the radiologic study, classification of the osteomyelitis of the jaw was made. Loclized osteolytic type was the highest in incidence (38.8%) and localized sclerotic type was the lowest (7.0%)

• Imaging Science in Dentistry
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• v.51 no.1
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• pp.9-16
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• 2021

Purpose: The purpose of this study was to analyze the reliability of 7 panoramic radiographic signs for predicting proximity of the root apices of mandibular third molars to the mandibular canal using cone-beam computed tomography and to correlate these findings with the Pell and Gregory and the Winter classification systems. Materials and Methods: An observational, cross-sectional, descriptive study was conducted on 74 patients with bilateral impacted mandibular third molars. Four panoramic radiographic signs were observed in the tooth root (darkening, deflection, and narrowing of the root apices, and bifid apices), and another 3 in the mandibular canal (diversion, narrowing, and interruption of the mandibular canal). Cone-beam computed tomography images were analyzed to identify disruption and diversion of the mandibular canal and root deflection. Results: Binary logistic regression showed that only 4 of the 7 panoramic radiographic signs were able to predict proximity of the root apices of the mandibular third molars to the mandibular canal: darkening of the root, deflection of the root, narrowing of the root, and interruption of the mandibular canal(P<0.05). Conclusion: Darkening, deflection, and narrowing of the root, in tandem with the interruption of the mandibular canal on panoramic radiographs, indicate that cone-beam computed tomography should be performed when planning the extraction of impacted mandibular third molars. Proximity between mandibular third molars and the mandibular canal is correlated with the Winter classification.