Results: All measurements showed great reproducibility with high intra-class reliability (>0.97). This resulted in the identification of 16 cephalometric landmarks, used for 16 angular and 2 linear measurements. The American Board of Orthodontics analysis and the European Board of Orthodontics analysis were used for the cephalometric measurements. All cephalometric X-rays were first manually traced using the Dolphin 3D Imaging program version 11.0 and then automatically, using the Artificial Intelligence CS imaging V8 software. The X-rays were taken in maximum image size (18 × 24 cm lateral image). Methods: A total of 100 cephalometric X-rays taken using a CS8100SC cephalostat were collected from a private practice. Background: This study aims to compare an automated cephalometric analysis based on the latest deep learning method of automatically identifying cephalometric landmarks with a manual tracing method using broadly accepted cephalometric software.
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