PURPOSE: The workflow for virtual surgical planning (VSP) and the application of CAD/CAM (computer-aided design/computer-aided manufacturing) procedures are mainly based on computed tomography (CT) derived DICOM data sets. Alternatively, this study a...
OBJECTIVE: To develop a machine-learning-based model and construct a nomogram that integrates ClinCheck features and clinical risk factors for accurately predicting open gingival embrasures (OGE) between mandibular central incisors after clear aligne...
BACKGROUND AND OBJECTIVES: Mandibular reconstruction following continuity resection due to tumor ablation or osteonecrosis remains a significant challenge in maxillofacial surgery. Virtual surgical planning (VSP) relies on accurate segmentation of th...
Age estimation is a crucial step in forensic identification, particularly in scenarios where dental structures may be absent. This study aimed to develop and evaluate supervised machine learning models to predict chronological age based on mandibular...
The mandible is one of the most reliable in sex determination in forensic anthropology. The shape of the mandible provides valuable information regarding the male and female distinctions. Machine learning algorithms are widely used for various applic...
BACKGROUND: Artificial intelligence (AI)-based cephalometric tracing has emerged as a promising tool that reduces operator variability and offers standardized, rapid, and reproducible assessments. This study aimed to evaluate the reliability and accu...
Conventional rigid grippers remain the most-used robotic grippers in industrial assembly tasks. However, they are limited in their ability to handle a diverse range of objects. This study draws inspiration from nature to address these limitations, em...
OBJECTIVES: Development and verification of a convolutional neural network (CNN)-based deep learning (DL) model for mandibular canal (MC) localization on multicenter cone beam computed tomography (CBCT) images.
Tonsilloliths can be seen on panoramic radiographs (PRs) as deposits located on the middle portion of the ramus of the mandible. Although tonsilloliths are clinically harmless, the high risk of misdiagnosis leads to unnecessary advanced examinations ...
The purpose of this study was to compare the performances of 2D, 2.5D, and 3D CNN-based segmentation networks, along with a 3D vision transformer-based segmentation network, for segmenting mandibular canals (MCs) on the public and external CBCT datas...
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