• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.23 no.1
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• pp.165-171
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• 1993

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.26 no.1
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• pp.7-14
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• 1996

• The Journal of Korean Academy of Prosthodontics
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• v.52 no.3
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• pp.233-238
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• 2014

Purpose: A method detecting change of jaw or alveolar bone density may be helpful in periodontal care, implant dentistry and evaluation of bone density of whole body. Materials and methods: In this study, bone density of intraoral periapical radiography using phantom-integrated XCP is compared with that of quantitative computed tomography (QCT). Results: Bone density of intraoral periapical radiography and the one measured by QCT showed high correlation (correlation coefficient = 0.92, P<.001) in alveolar bone, and relatively high correlation (0.73, P<.001) in cancellous bone. Conclusion: This study revealed possibility of scoring of bone density by intraoral periapical radiography.

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.267-273
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• 2024

Using a cloud-based vertex AI platform that can develop an artificial intelligence learning model without coding, this study easily developed an artificial intelligence learning model by the non-professional general public and confirmed its clinical applicability. Nine dental diseases and 2,999 root disease X-ray images released on the Kaggle site were used for the learning data, and learning, verification, and test data images were randomly classified. Image classification and multi-label learning were performed through hyper-parameter tuning work using a learning pipeline in vertex AI's basic learning model workflow. As a result of performing AutoML(Automated Machine Learning), AUC(Area Under Curve) was found to be 0.967, precision was 95.6%, and reproduction rate was 95.2%. It was confirmed that the learned artificial intelligence model was sufficient for clinical diagnosis.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.110-116
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• 2010

Purpose: The X-ray attenuation coefficient based on CT images is used for attenuation correction in PET/CT. The polychromatic X-ray beam can introduce beam-hardening artifact on CT images. The aims of the study were to evaluate the effect of dental metal prostheses in phantom and patients on apparent tracer activity measured with PET/CT when using CT attenuation correction. Materials and Methods: 40 normal patients (mean age $54{\pm}12$) was scanned between Jan and Feb 2010. NEMA(National Electrical Manufactures Association) PET $Phantom^{TM}$ (NU2-1994) was filled with $^{18}F$-FDG injected into the water that insert implant and metal prostheses dental cast. Region of interest were drawn in non-artifact region, bright steak artifact region and dark streak artifact region on the same transaxial CT and PET slices. Patients and phantom with dental metal prostheses and dental implant were evaluated the change rate of CT Number and $SUV_{mean}$ in PET/CT. A paired t-test was performed to compare the ratio and the difference of the calculated values. Results: In patients with dental metal prostheses, $SUV_{mean}$ was reduced 19.64% (p<0.05) in the non-steak artifact region than the brightstreak artifact region whereas was increased 90.1% (p>0.05) in the non-steak artifact region than the dark streak artifact region. In phantom with dental metal prostheses, $SUV_{mean}$ was reduced 18.1% (p<0.05) in the non-steak artifact region than the bright streak artifact region whereas was increased 18.0% (p>0.05) in the non-steak artifact region than the dark streak artifact region. In patients with dental implant, $SUV_{mean}$ was increased 19.1% (p<0.05) in the non-steak artifact region than the bright streak artifact region whereas was increased 96.62% (p>0.05) in the non-steak artifact region than the dark streak artifact region. In phantom with dental implant, $SUV_{mean}$ was increased 14.4% (p<0.05) in the non-steak artifact region than the bright streak artifact region whereas was increased 7.0% (p>0.05) in the non-steak artifact region than the dark streak artifact region. Conclusion: When CT is used for attenuation correction in patients with dental metal prostheses, 19.1% reduced $SUV_{mean}$ is anticipated in the dark streak artifact region on CT images. The dark streak artifacts of CT by dental metal prostheses may cause false negative finding in PET/CT. We recommend that the non-attenuation corrected PET images also be evaluated for clinical use.

• Journal of the korean academy of Pediatric Dentistry
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• v.39 no.3
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• pp.249-256
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• 2012

Cone beam computed tomography (CBCT) has become widely available in recent years and is recognized as an important diagnostic tool for varies disease and condition of the orofacial structure. Clinician is easy to determine adequate treatment plan for pediatric patients by using CBCT. CBCT is used in Chonbuk National University Dental Hospital since 2005. This research presents clinical application of CBCT on patients visiting department of pediatric dentistry in Chonbuk National University Dental Hospital from Jan, 2005 to July, 2011. 1. Total number of patients taken CBCT is 252, and total number of area taken CBCT is 279. 2. An age group form 9 years to 12 years showing 53% was highest and percentage of 6~8 years showed 24%. 3. Chief complaints for CBCT taking are position and shape of impacted teeth (49.1%), mesiodens (19.4%), supernumerary teeth (7.9%), position and root canal shape of erupting teeth (7.2%), cyst (5.4%), inflammatory lesion (3.9%), odontoma (3.9%), tumor (2.2%), and et al. 4. Treatments are extraction (29.7%), orthodontic traction and leveling (24.0%), follow up (16.5%), refer to other professional part (11.5%), endodontic treatment (3.9%), surgical removal (2.9%), malsupialization (3.9%), enucleation (1.1%), and fail to follow up (5.0%), and et al.

• Journal of Oral Medicine and Pain
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• v.34 no.1
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• pp.81-90
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• 2009

This study is designed to assess Relationship between clinical diagnosis of Temporomandibular Joint Disorder and diagnostic finding of Cone Beam Computed Tomography(CBCT) The author performed clinical examination for TMD Patients who visited Orofacial pain clinic, Jin-ju ooo Dental office. CBCT(Cone beam computed tomography) was taken for 190 joints in 95 subjects. A Oral medicine and Oral radiologist evaluated CBCT each other. then we compared with that result, Condyle bony changes were classified by no bone change, flattening, erosion and osteophyte. The obtained results were as follow: 1. The Kappa index of the diagnosis between oral medicine and oral radiogist were high, the index of diagnosis by degenerative joint disease were more higher. 2. The Kappa index of panoramic view and CBCT was low, more condylar bone chages were observed by CBCT diagnosis 3. Condylar bone changes of the 54.2% of non-DJD group clinicaly was observed by CBCT diagnosis and no bone changes of the 15.3% of DJD group.was observed by CBCT 4. TMJ pain was associated with erosion of condyle bone change of TMJ. Crepitation and longest duration of TMD were associated with osteophytic bone change.

• Journal of the korean academy of Pediatric Dentistry
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• v.48 no.2
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• pp.221-228
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• 2021

The aim of this study was to evaluate the use of easily accessible machine learning application to identify mesiodens, and to compare the ability to identify mesiodens between trained model and human. A total of 1604 panoramic images (805 images with mesiodens, 799 images without mesiodens) of patients aged 5 - 7 years were used for this study. The model used for machine learning was Google's teachable machine. Data set 1 was used to train model and to verify the model. Data set 2 was used to compare the ability between the learning model and human group. As a result of data set 1, the average accuracy of the model was 0.82. After testing data set 2, the accuracy of the model was 0.78. From the resident group and the student group, the accuracy was 0.82, 0.69. This study developed a model for identifying mesiodens using panoramic radiographs of children in primary and early mixed dentition. The classification accuracy of the model was lower than that of the resident group. However, the classification accuracy (0.78) was higher than that of dental students (0.69), so it could be used to assist the diagnosis of mesiodens for non-expert students or general dentists.

• Journal of the korean academy of Pediatric Dentistry
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• v.44 no.2
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• pp.129-137
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• 2017

The aim of this study was to enhancing the panoramic radiograph's clinical use for assessing mandibular measurements and formulating a function of those measurements from panoramic radiographs and lateral cephalograms in children. The panoramic radiographs and lateral cephalograms of 99 former orthodontic patients with skeletal class III malocclusion were selected. In each radiograph, gonial angles, ramus heights, and distance between lower incisors and symphysis were measured. The values of the studied parameters were compared by paired t-test, Pearson's correlation test and regression analysis. The mean value of the gonial angle in panoramic radiographs was $125.49^{\circ}$, and the value in lateral cephalograms was $127.50^{\circ}$. The Pearson's correlation coefficient (${\rho}$) between mean values of gonial angle in each radiograph was 0.945 (p < 0.001). The relationship between the gonial angle measurements obtained from each radiographs was represented as 'Gonial angle (Lateral cephalograms) = 0.920 ${\times}$ Average gonial angle (Panoramic radiographs) + 12.072' in the linear function. The coefficients of ramus heights, and distance between lower incisors and symphysis portrayed weaker correlations than gonial angles. A panoramic radiograph could be used to determine the gonial angle as accurately as a lateral cephalogram, and each gonial angle showed a strong positive relation. A panoramic radiograph is a useful tool for examining vertical growth pattern of patients, as well as a lateral cephalogram.

• The korean journal of orthodontics
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• v.41 no.4
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• pp.255-267
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• 2011

Objective: The purpose of this study was to confirm the reliability of a cone beam computed tomography (CBCT)-generated panoramic view based on a CBCT 3D image and to find the most helpful 2D panoramic image compared with CBCT 3D image when examining the mesiodistal tooth axis. Methods: A test model was constructed according to cephalometric norms. The test model was repeatedly repositioned for CBCT and panoramic radiographic imaging. Panoramic radiographs were acquired at each of the following 3 occlusal plane positions: $-5^{\circ}$, $0^{\circ}$, and $+5^{\circ}$. Measurements of mesiodistal tooth axis in CBCT 3D image, CBCT-generated panoramic view, and panoramic radiographs were compared. Results: Compared with the CBCT-generated panoramic view, CBCT 3D image showed significant difference in the mesiodistal tooth axis in the premolars and no significant difference in the mesiodistal tooth axis in the incisors and canines. Mesiodistal tooth axis on the CBCT-generated panoramic view was significantly different from that on panoramic radiographs. Conclusions: CBCT-generated panoramic view can be a useful tool for evaluating mesiodistal tooth axis.