INTRODUCTION AND AIMS: Artificial intelligence (AI) has been adopted in the field of dental restoration. This study aimed to evaluate the time efficiency and morphological accuracy of crowns designed by two AI-powered software programs in comparison ...
Monolithic zirconia (MZ) crowns are widely utilized in dental restorations, particularly for substantial tooth structure loss. Inspection, tactile, and radiographic examinations can be time-consuming and error-prone, which may delay diagnosis. Conseq...
BACKGROUND: In recent years, artificial intelligence (AI) has made remarkable advancements and achieved significant accomplishments across the entire field of dentistry. Notably, efforts to apply AI in prosthodontics are continually progressing. This...
OBJECTIVES: This study aimed to compare the design outcomes of anterior crowns generated using deep learning (DL)-based software with those fabricated by a technician using conventional dental computer-assisted design (CAD) software without DL suppor...
Designing dental crowns with computer-aided design software in dental laboratories is complex and time-consuming. Using real clinical datasets, we developed an end-to-end deep learning model that automatically generates personalized dental crown mesh...
The generation of depth images of occlusal dental crowns is complicated by the need for customization in each case. To decrease the workload of skilled dental technicians, various computer vision models have been used to generate realistic occlusal c...
Fiber posts present significant challenges for nonsurgical endodontic retreatment, as improper removal may result in iatrogenic root perforation or even root fracture. Recently, robotic technology has attracted considerable attention in dentistry and...
OBJECTIVE: This study evaluated ResNet-50 and U-Net models for detecting and segmenting vertical misfit in dental implant crowns using periapical radiographic images.