To develop and validate an artificial intelligence (AI)-driven tool for the automatic segmentation of pulp cavity structures in maxillary premolars teeth on cone-beam computed tomography (CBCT). One hundred and eleven CBCT scans were divided into tra...
OBJECTIVE: This study aimed to predict long-term growth-related changes in skeletal and dental relationships within the craniofacial complex using machine learning (ML) models.
PURPOSE: Artificial intelligence (AI) may be used to learn and predict the maxillomandibular relationship, particularly when the number of occluding teeth pairs is insufficient. This study aimed to investigate the feasibility of training a new two-st...
OBJECTIVES: This study developed and evaluated a two-stage deep learning-based system for automatic segmentation of mandibular cortical bone, mandibular cancellous bone, maxillary cortical bone and maxillary cancellous bone on cone beam computed tomo...
OBJECTIVES: To assess the feasibility and accuracy of a new prototype robotic implant system for the placement of zygomatic implants in edentulous maxillary models.
Journal of prosthodontics : official journal of the American College of Prosthodontists
Nov 12, 2024
Pterygoid implant placement has been proven to be a viable option in full-arch implant rehabilitation for extremely atrophic maxillae. Nevertheless, the utilization of pterygoid implants remains a challenge for the dentist due to the difficulties of ...
Journal of the World federation of orthodontists
Nov 2, 2024
INTRODUCTION: Advancements in technology have led to the adoption of digital workflows in dentistry, which require the segmentation of regions of interest from cone-beam computed tomography (CBCT) scans. These segmentations assist in diagnosis, treat...
OBJECTIVES: To evaluate and compare the accuracy of task-autonomous robot-assisted implant surgery (RAIS) and dynamic computer-assisted implant surgery (dCAIS) for zygomatic implant placement.
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