Korea University · 歯学
Professor Seok-Ki Jung's research lab specializes in the application of artificial intelligence and deep learning to orthodontic diagnosis and treatment planning. The lab focuses on developing convolutional neural network models to analyze cephalometric radiographs, intraoral photographs, and clinical data for automated classification of orthodontic conditions, such as surgical indications and dental crowding. A key emphasis is on improving diagnostic accuracy through interpretable AI techniques like Grad-CAM for visualizing model decision-making. The lab also investigates the biomechanical influences of orofacial muscle function on dentofacial morphology, integrating clinical measurements with imaging analysis.
Figures are computed from collected data and may differ slightly.
The aim of this study was to investigate the relationship between image patterns in cephalometric radiographs and the diagnosis of orthognathic surgery and propose a method to improve the accuracy of predictive models according to the depth of the neural networks. The study included 640 and 320 patients requiring non-surgical and surgical orthodontic treatments, respectively. The data of 150 patients were exclusively classified as a test set. The data of the remaining 810 patients were split int
The aim of this study was to evaluate the deep convolutional neural networks (DCNNs) based on analysis of cephalometric radiographs for the differential diagnosis of the indications of orthognathic surgery. Among the DCNNs, Modified-Alexnet, MobileNet, and Resnet50 were used, and the accuracy of the models was evaluated by performing 4-fold cross validation. Additionally, gradient-weighted class activation mapping (Grad-CAM) was used to perform visualized interpretation to determine which region
Determining the severity of dental crowding and the necessity of tooth extraction for orthodontic treatment planning are time-consuming processes and there are no firm criteria. Thus, automated assistance would be useful to clinicians. This study aimed to construct and evaluate artificial intelligence (AI) systems to assist with such treatment planning. A total of 3,136 orthodontic occlusal photographs with annotations by two orthodontists were obtained. Four convolutional neural network (CNN) m
An artificial intelligence system that utilizes deep learning with proper training models can successfully classify orthodontic facial and intraoral photos automatically. This technique can be used for the first step of a fully automated orthodontic diagnostic system in the future.
The aim of this study was to evaluate the effects of the tongue and lip pressure on dentofacial morphology. The subjects comprised 194 patients with malocclusion. Anterior and posterior tongue elevation and lip pressures were evaluated using the Iowa Oral Performance Instrument (IOPI) device. The lateral cephalograms of each subject were traced and digitized to perform the analysis. Statistical analysis was used to investigate the relationship between perioral muscle force and the cephalometric
Altered sleep patterns caused by shift work have more influence on periodontal disease than sleep duration.
The aim of this study was to present a control method for modulating the translucency of lithium disilicate ceramics through thermal refinement. Identical lithium disilicate blocks were thermally refined using four different heat treatment schedules, and the microstructure, translucency, and flexural strength of the ceramics were investigated in detail by SEM, spectroscopy, and a piston-on-three-ball test. The results showed that ceramics treated under higher heat had larger grains, with an aver
The aim of this study was to assess the changes in individual condyles from 5 to 8 years in patients with temporomandibular joint (TMJ) osteoarthritis using 3-dimensional cone beam computed tomography (3D CBCT) reconstruction and superimposition. To assess the longitudinal TMJ changes, CBCT was performed at initial (T<sub>0</sub>) and final (T<sub>2</sub>) timepoints that were at least 5 years apart and at a middle (T<sub>1</sub>) timepoint. To improve the accuracy, we used a novel superimpositi
(1) Background: The purpose of this study was to evaluate the 3-dimensional bony changes of the mandibular condyle in temporomandibular joints-osteoarthritis (TMJ-OA) patients treated with stabilization splint (SS) therapy using shape correspondence analysis. (2) Methods: A total of 27 adult patients (2 men and 25 women) with a mean age of 24.6 ± 3.9 years were included in this study. All patients were diagnosed with TMJ-OA and were treated with an SS. Cone-beam computed tomography data of the c
The aim of this study was to measure the bone mineral density of specific regions of maxilla, mandible, and first cervical vertebra using the Hounsfield unit and trabecular microstructure pattern analysis and to compare the two methods. In this study, cone-beam computed tomography (CBCT) images were obtained from 58 patients. Trabecular thickness, trabecular number, trabecular separation, and bone volume fraction were measured in 484 regions for trabecular microstructure parameters and Hounsfiel
The aim of this study was to evaluate the three-dimensional reproducibility of the structured-light facial scanner according to the head position change. A mannequin head was used and angle of the mannequin's axis-orbital plane to the true horizontal plane was adjusted to +10, +5, 0, -5, and -10°. Facial scanning was conducted 30 times, respectively, and 150 3D images were obtained. Reoriented landmarks of each group were compared and analyzed. Reproducibility decreased as the distance from the
To assess the incidence of and risk factors for black triangles between the central incisors after orthodontic treatment; Methods: Ninety-seven post-treatment patients (29 men and 68 women; mean age, 22.7 years) were retrospectively divided into two groups based on the presence or absence of black triangles, using intraoral photographs. Based on the Jemt Index, the black triangle occurrence group was further classified into mild, moderate, and severe groups. Parameters from periapical radio grap
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