김윤지 교수

The purpose of this study was to develop a diagnostic tool to automatically detect temporomandibular joint osteoarthritis (TMJOA) from cone beam computed tomography (CBCT) images with artificial intelligence. CBCT images of patients diagnosed with temporomandibular disorder were included for image preparation. Single-shot detection, an object detection model, was trained with 3,514 sagittal CBCT images of the temporomandibular joint that showed signs of osseous changes in the mandibular condyle.

Prediction of hand-wrist SMI based on CV images is possible using machine learning methods. Chronological age and sex increased the prediction accuracy. An automated diagnosis of the skeletal maturation may aid as a decision-supporting tool for evaluating the optimal treatment timing for growing patients.

Various AI algorithms developed for diagnosing TMDs may provide additional clinical expertise to increase diagnostic accuracy. However, it should be noted that a high risk of bias was present in the included studies. Also, certainty of evidence was very low. Future research of higher quality is strongly recommended.

The use of intraoral scanners in the field of dentistry is increasing. In orthodontics, the process of tooth segmentation and rearrangement provides the orthodontist with insights into the possibilities and limitations of treatment. Although, full-arch scan data, acquired using intraoral scanners, have high dimensional accuracy, they have some limitations. Intraoral scanners use a stereo-vision system, which has difficulties scanning narrow interdental spaces. These areas, with a lack of accurat

Orthodontic tooth setup provides the orthodontist an insight into the possibilities and limitations of treatment and enables visualization of the final goal of treatment. Lately, artificial intelligence techniques have been applied to the digital setup software to automate the process of tooth segmentation and alignment. The purpose of this study was to evaluate the accuracy and efficiency of automated digital setup software. The diagnostic digital impression data of 30 patients (mean age, 29.8

After second molar protraction into the missing first molar or second premolar space, mandibular second molars may exhibit alveolar bone resorption in the distal root in older patients and in those with mesially tilted third molars before treatment.

: Our findings support the positive outcomes of orthognathic surgery in the treatment of facial asymmetry in terms of skeletal and soft tissue improvements, stability, relief of TMD symptoms, and enhancement of QoL. However, most of the included studies showed a low certainty of evidence and high heterogeneity.

The errors in landmark positions, especially those that define reference planes, may significantly affect cephalometric measurements. The possibility of errors generated by automated lateral cephalometric analysis systems should be considered when using such systems for orthodontic diagnoses.

In contemporary practice, intraoral scans and cone-beam computed tomography (CBCT) are widely adopted techniques for tooth localization and the acquisition of comprehensive three-dimensional models. Despite their utility, each dataset presents inherent merits and limitations, prompting the pursuit of an amalgamated solution for optimization. Thus, this research introduces a novel 3D registration approach aimed at harmonizing these distinct datasets to offer a holistic perspective. In the pre-pro

Our findings provided detailed information on work practices, number of procedures performed on a weekly basis, and occupational radiation doses, which enabled in-depth evaluation of occupational radiation exposure and work status among dentists.

Greater third molar mesialization was observed when Nolla's stage of the third molar was higher before treatment and when the second molar protraction time was longer.