• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.27 no.1
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• pp.99-106
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• 1997

The purpose of this study was to compare & to find out the variability of head film measurements (and marks identification) between Fuji computed radiographic cephalometry and conventional cephalometry. 28 Korean adults were selected. Lateral cephalometric FCR film and conventional cephalometric film of each subject was taken. Four investigators identified 24 cephalometric landmarks on lateral cephalometric FCR film and conventional cephalometric film. The comparable measurements between lateral cephalometric FCR film and conventional cephalometric film were statistically analysed. The results were as follows : 1. In FCR film & conventional film, coefficient of variation (C.V.) of 24 landmarks was taken horizonta1ly & vertically. There is no significant difference of rank order of landmarks in C.V. between two films. 2. In comparison of significant differences of landmarks variability between FCR film & conventional film, horizontal value of coefficient of variation, showed significant differences in four landmarks among twenty-four landmarks, but vertical value of coefficient of variation showed significant differences in sixteen landmarks among twenty-four landmarks. FCR film showed significantly less variability than conventional film in 17 subjects among 20(4+16) subjects that showed significant difference.

• Imaging Science in Dentistry
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• v.51 no.3
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• pp.299-306
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• 2021

Purpose: This study aimed to propose a fully automatic landmark identification model based on a deep learning algorithm using real clinical data and to verify its accuracy considering inter-examiner variability. Materials and Methods: In total, 950 lateral cephalometric images from Yonsei Dental Hospital were used. Two calibrated examiners manually identified the 13 most important landmarks to set as references. The proposed deep learning model has a 2-step structure-a region of interest machine and a detection machine-each consisting of 8 convolution layers, 5 pooling layers, and 2 fully connected layers. The distance errors of detection between 2 examiners were used as a clinically acceptable range for performance evaluation. Results: The 13 landmarks were automatically detected using the proposed model. Inter-examiner agreement for all landmarks indicated excellent reliability based on the 95% confidence interval. The average clinically acceptable range for all 13 landmarks was 1.24 mm. The mean radial error between the reference values assigned by 1 expert and the proposed model was 1.84 mm, exhibiting a successful detection rate of 36.1%. The A-point, the incisal tip of the maxillary and mandibular incisors, and ANS showed lower mean radial error than the calibrated expert variability. Conclusion: This experiment demonstrated that the proposed deep learning model can perform fully automatic identification of cephalometric landmarks and achieve better results than examiners for some landmarks. It is meaningful to consider between-examiner variability for clinical applicability when evaluating the performance of deep learning methods in cephalometric landmark identification.

• The korean journal of orthodontics
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• v.51 no.2
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• pp.77-85
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• 2021

Objective: To evaluate the accuracy of a multi-stage convolutional neural network (CNN) model-based automated identification system for posteroanterior (PA) cephalometric landmarks. Methods: The multi-stage CNN model was implemented with a personal computer. A total of 430 PA-cephalograms synthesized from cone-beam computed tomography scans (CBCT-PA) were selected as samples. Twenty-three landmarks used for Tweemac analysis were manually identified on all CBCT-PA images by a single examiner. Intra-examiner reproducibility was confirmed by repeating the identification on 85 randomly selected images, which were subsequently set as test data, with a two-week interval before training. For initial learning stage of the multi-stage CNN model, the data from 345 of 430 CBCT-PA images were used, after which the multi-stage CNN model was tested with previous 85 images. The first manual identification on these 85 images was set as a truth ground. The mean radial error (MRE) and successful detection rate (SDR) were calculated to evaluate the errors in manual identification and artificial intelligence (AI) prediction. Results: The AI showed an average MRE of 2.23 ± 2.02 mm with an SDR of 60.88% for errors of 2 mm or lower. However, in a comparison of the repetitive task, the AI predicted landmarks at the same position, while the MRE for the repeated manual identification was 1.31 ± 0.94 mm. Conclusions: Automated identification for CBCT-synthesized PA cephalometric landmarks did not sufficiently achieve the clinically favorable error range of less than 2 mm. However, AI landmark identification on PA cephalograms showed better consistency than manual identification.

• Imaging Science in Dentistry
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• v.45 no.3
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• pp.175-180
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• 2015

Purpose: This study was performed to evaluate the reliability of the identification of anatomical landmarks in panoramic and lateral cephalometric radiographs on a standard medical grade picture archiving communication system (PACS) monitor and a tablet computer (iPad 5). Materials and Methods: A total of 1000 radiographs, including 500 panoramic and 500 lateral cephalometric radiographs, were retrieved from the de-identified dataset of the archive of the Section of Oral and Maxillofacial Radiology of the University Of Connecticut School Of Dental Medicine. Major radiographic anatomical landmarks were independently reviewed by two examiners on both displays. The examiners initially reviewed ten panoramic and ten lateral cephalometric radiographs using each imaging system, in order to verify interoperator agreement in landmark identification. The images were scored on a four-point scale reflecting the diagnostic image quality and exposure level of the images. Results: Statistical analysis showed no significant difference between the two displays regarding the visibility and clarity of the landmarks in either the panoramic or cephalometric radiographs. Conclusion: Tablet computers can reliably show anatomical landmarks in panoramic and lateral cephalometric radiographs.

• The korean journal of orthodontics
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• v.32 no.1 s.90
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• pp.59-69
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• 2002

The purpose of this study was to evaluate the reproducibility of lateral cephalometric landmarks according to radiographic image enhancement, and to contribute to the identification of cephalometric landmarks. Lateral cephalograms of ten individuals were taken and stored into computer. The images were then enhanced up to four grades by Quick Ceph Image Pro$^{TM}$ on condition that the gray-scale equalization number was 50 and the detail enhancement number was 50. After thirty two landmarks were identified on monitor images by five observers, the deviations from the mean, the distances estimated between identified points and the mean point of five identified points, were evaluated for each landmark at each enhancement grade. Through the statistical analysis, following results were obtained. 1. In case of unenhanced radiographic images, the inter-observer reproducibility of the landmarks showed a large variation. 2. The comparison of deviation from the mean according to the degree of radiographic image enhancement for each landmark showed that the inter-observer reproducibility was significantly different at 5 landmarks. 3. The landmark of pterygomaxillary fissure showed higher reproducibility at enhancement grade 1 and 2 images than at unenhanced images. So did the landmark of posterior nasal spine at enhancement grade 1 images, and the landmark of menton at enhancement grade 2, 3 and 4 images respectively. The above results suggest that the reproducibility of some landmarks can be increased by radiographic image enhancement during the identification of the lateral cephalometric landmarks on the monitor.

• Imaging Science in Dentistry
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• v.45 no.4
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• pp.213-220
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• 2015

Purpose: The aim this study was to compare the accuracy of orthodontists and dentomaxillofacial radiologists in identifying 17 commonly used cephalometric landmarks, and to determine the extent of variability associated with each of those landmarks. Materials and Methods: Twenty digital lateral cephalometric radiographs were evaluated by two groups of dental specialists, and 17 cephalometric landmarks were identified. The x and y coordinates of each landmark were recorded. The mean value for each landmark was considered the best estimate and used as the standard. Variation in measurements of the distance between landmarks and measurements of the angles associated with certain landmarks was also assessed by a subset of two observers, and intraobserver and interobserver agreement were evaluated. Results: Intraclass correlation coefficients were excellent for intraobserver agreement, but only good for interobserver agreement. The least reliable landmark for orthodontists was the gnathion (Gn) point (standard deviation [SD], 5.92 mm), while the orbitale (Or) was the least reliable landmark (SD, 4.41 mm) for dentomaxillofacial radiologists. Furthermore, the condylion (Co)-Gn plane was the least consistent (SD, 4.43 mm). Conclusion: We established that some landmarks were not as reproducible as others, both horizontally and vertically. The most consistently identified landmark in both groups was the lower incisor border, while the least reliable points were Co, Gn, Or, and the anterior nasal spine. Overall, a lower level of reproducibility in the identification of cephalometric landmarks was observed among orthodontists.

• The korean journal of orthodontics
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• v.32 no.2 s.91
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• pp.79-89
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• 2002

The purpose of this study is to evaluate the reproducibility and errors in landmark identification of conventional lateral cephalometric radiography and digital lateral cephalometric radiography. Fifteen conventional lateral cephalometric radiographs and fifteen digital lateral cephalometric radiographs were selected in adults with no considerations on sex and craniofacial forms. Each landmark was identified and expressed as the coordinate (x, y). The landmarks were classified into 3 groups. The landmarks of the first identification was T1, identification after one week was T2, and identification after one month was T3. The mean and standard deviation of identification errors between replicates were calculated according to the x and y coordinates. The errors between first identification and second identification were expressed as T2-T1(x), T2-T1(y) and those between first identification and third identification were expressed as T3-T1(x), T2-T1(y). Each was divided into conventional lateral cephalometric radiography and digital lateral cephalometric radiography. The independent t- test was used for statistical analysis of identification errors for the evaluation of reproducibility. The results of this study were as follows ; 1. Generally, the mean and standard deviation of landmark identification errors in digital lateral cephalometric radiography was smaller than those of conventional lateral cephalometric radiography. 2. Only a few landmarks showed statistically significant difference in identification error between conventional lateral cephalometric radiography and digital lateral cephalometric radiography. 3. The enhancement of image quality didn't guarantee decrease in landmark identification error and didn't affect tendency of landmark identification error.

• The korean journal of orthodontics
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• v.49 no.1
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• pp.41-48
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• 2019

Objective: This in-vivo study aimed to compare landmark identification errors in anteroposterior (AP) and posteroanterior (PA) cephalograms generated from cone-beam computed tomography (CBCT) scan data in order to examine the feasibility of using AP cephalograms in clinical settings. Methods: AP and PA cephalograms were generated from CBCT scans obtained from 25 adults. Four experienced and four inexperienced examiners were selected depending on their experience levels in analyzing frontal cephalograms. They identified six cephalometric landmarks on AP and PA cephalograms. The errors incurred in positioning the cephalometric landmarks on the AP and PA cephalograms were calculated by using the straight-line distance and the horizontal and vertical components as parameters. Results: Comparison of the landmark identification errors in CBCT-generated frontal cephalograms revealed that landmark-dependent differences were greater than experienceor projection-dependent differences. Comparisons of landmark identification errors in the horizontal and vertical directions revealed larger errors in identification of the crista galli and anterior nasal spine in the vertical direction and the menton in the horizontal direction, in comparison with the other landmarks. Comparison of landmark identification errors between the AP and PA projections in CBCT-generated images revealed a slightly higher error rate in the AP projections, with no inter-examiner differences. Statistical testing of the differences in landmark identification errors between AP and PA cephalograms showed no statistically significant differences for all landmarks. Conclusions: The reproducibility of CBCT-generated AP cephalograms is comparable to that of PA cephalograms; therefore, AP cephalograms can be generated reliably from CBCT scan data in clinical settings.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.36 no.4
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• pp.262-269
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• 2010

Introduction: Accurate diagnosis and treatment planning are very important for orthognathic surgery. A small error in diagnosis can cause postoperative functional and esthetic problems. Pre-existing 2-dimensional (D) chephalogram analysis has a high likelihood of error due to its intrinsic and extrinsic problems. A cephalogram can also be inaccurate due to the limited anatomic points, superimposition of the image, and the considerable time and effort required. Recently, an improvement in technology and popularization of computed tomography (CT) provides patients with 3-D computer based cephalometric analysis, which complements traditional analysis in many ways. However, the results are affected by the experience and the subject of the investigator. Materials and Methods: The effects of the sources human error in 2-D cephalogram analysis and 3-D computerized tomography cephalometric analysis were compared using Simplant CMF program. From 2008 Jan to 2009 June, patients who had undergone CT, cephalo AP, lat were investigated. Results: 1. In the 3 D and 2 D images, 10 out of 93 variables (10.4%) and 11 out 44 variables (25%), respectively, showed a significant difference. 2. Landmarks that showed a significant difference in the 2 D image were the points frequently superimposed anatomically. 3. Go Po Orb landmarks, which showed a significant difference in the 3 D images, were found to be the artificial points for analysis in the 2 D image, and in the current definition, these points cannot be used for reproducibility in the 3 D image. Conclusion: Generally, 3-D CT images provide more precise identification of the traditional cephalometric landmark. Greater variability of certain landmarks in the mediolateral direction is probably related to the inadequate definition of the landmarks in the third dimension.

• Journal of the korean academy of Pediatric Dentistry
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• v.48 no.3
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• pp.245-254
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• 2021

The aim of this study was to evaluate the accuracy of 3 different automatic landmark identification programs on lateral cephalgrams and the clinical acceptability in pediatric dentistry. Sixty digital cephalometric radiographs of 7 to 12 years old healthy children were randomly selected. Fourteen landmarks were chosen for assessment and the mean of 3 measurements of each landmark by a single examiner was defined as the baseline landmarks. The mean difference between an automatically identified landmark and the baseline landmark was measured for each landmark on each image. The total mean difference of 3 automatic programs compared to the baseline landmarks were 2.53 ± 1.63 mm. Errors among 3 programs were not significantly different for 12 of 14 landmarks except Orbitale and Gonion. The automatic landmark identification programs showed significant higher mean detection errors than the manual method. The programs couldn't be used as the 1st tool to replace human examiners. But considering short consuming time, these results indicate that all 3 programs have sufficient validity to be used in pediatric dental clinic.