How reliable are AI-Assisted cephalometric programs in assessing measurements involving bilateral landmarks?
Publié en ligne: 19 juin 2025
Pages: 123 - 129
Reçu: 01 sept. 2024
Accepté: 01 mars 2025
DOI: https://doi.org/10.2478/aoj-2025-0017
Mots clés
© 2025 Hakan Gurcan Gurel et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Objective
Recent advancements in technology have promoted artificial intelligence (AI) to automatically detect landmarks on lateral cephalograms. This study aimed to evaluate the reliability of an AI-assisted cephalometric analysis program (Webceph, Gyeonggi-do, Republic of Korea) in the assessment of cephalometric measurements involving bilateral landmarks.
Materials and methods
Fifty-one high-quality cephalograms were used and inclusion/exclusion criteria were applied. Two researchers manually traced the cephalograms after which an AI-assisted cephalometric analysis program (Webceph) was applied. Both intra-and inter-operator reliability were tested. Independent Sample t-tests were used to compare the means of measurements.
Results
The inter- and intra-class correlation coefficients were 0.80 which indicated ‘good’ reliability. Statistically significant differences were found in the gonial angle and effective mandibular length measurements (
Conclusion
AI-driven cephalometric analysis holds promise for improving diagnostic efficiency and precision. However, limitations and further AI advancements require consideration to ensure appropriate clinical use.