Objectives: To investigate the current clinical applications and diagnostic performance of
artificial intelligence (AI) in dental and maxillofacial radiology (DMFR). Methods: Studies …

In the last few years, artificial intelligence (AI) research has been rapidly developing and
emerging in the field of dental and maxillofacial radiology. Dental radiography, which is …

Objectives To compare detection patterns of 80 cephalometric landmarks identified by an
automated identification system (AI) based on a recently proposed deep-learning method …

Background: Cephalometric analysis has long been, and still is one of the most important
tools in evaluating craniomaxillofacial skeletal profile. To perform this, manual tracing of x …

This study aimed to analyze the existing literature on how artificial intelligence is being used
to support the identification of cephalometric landmarks. The systematic analysis of literature …

The lengthy time needed for manual landmarking has delayed the widespread adoption of
three-dimensional (3D) cephalometry. We here propose an automatic 3D cephalometric …

Introduction This article presents a novel technique for automatic cephalometric landmark
localization on 3-dimensional (3D) cone-beam computed tomography (CBCT) volumes by …

Objectives To determine the optimal quantity of learning data needed to develop artificial
intelligence (AI) that can automatically identify cephalometric landmarks. Materials and …

Using computer vision through artificial intelligence (AI) is one of the main technological
advances in dentistry. However, the existing literature on the practical application of AI for …

Introduction Cone-beam computed tomography (CBCT) is commonly used for 3-dimensional
(3D) evaluation and treatment planning of patients in orthodontics, where precision and …