Akademik Veri Yönetim Sistemi
Orthodontics and Craniofacial Research, cilt.26, sa.3, ss.481-490, 2023 (SCI-Expanded)
Objective: The aim of this study is to evaluate whether fully automatic cephalometric analysis software with artificial intelligence algorithms is as accurate as non-automated cephalometric analysis software for clinical diagnosis and research. Materials and Methods: This is a retrospective archive study using lateral cephalometric radiographs taken from individuals aged 12-20 years. Cephalometric measurement data were obtained from these lateral cephalometric radiographs by manual landmark marking with non-automated computer software (Dolphin 11.8). Again, the same radiographs were made using fully automatic digital cephalometric analysis software OrthoDx™ (AI-Powered Orthodontic Imaging System, Phimentum) and WebCeph (Assemblecircle, Seoul, Korea) with artificial intelligence algorithm, without manual intervention of the researcher and fully automatic markings and measurements were made by the software. Results: According to the consistency test, a statistically significant good level of consistency was found between Dolphin and OrthoDx™ measurements and Dolphin and WebCeph measurements in angular measurements (ICC > 0.75, P <.01, ICC > 0.75, P < 0, respectively. 01). A weak level of consistency was found in linear measurement and soft tissue parameters in both software (ICC < 0.50, P <.05, ICC < 0.50, P <.05), and the difference between measurements was statistically found to be different from “0.”. Conclusion: The results obtained from fully automatic cephalometric analysis software with artificial intelligence algorithms are similar to the results of non-automated cephalometric analysis software, although there are differences in some parameters. To minimize the margin of error in artificial intelligence-based fully automatic cephalometric software, the manual intervention of the observer is needed.