Reliability of Artificial Intelligence in Lateral Cephalometric Analysis
| Autor: | Nouran Hesham Emad, Mostafa Ashmawy, Sahar Samir |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Ain Shams Dental Journal, Vol 33, Iss 1, Pp 61-71 (2024) |
| Druh dokumentu: | article |
| ISSN: | 1110-7642 2735-5039 |
| DOI: | 10.21608/asdj.2024.260733.1200 |
| Popis: | Objectives: The purpose of this study was to assess the reliability of lateral cephalometric analysis performed by an artificial intelligence-dependent software program.Methods: One Hundred and Eighty digital cephalometric radiographs acquired by Vatech PaX-i X-ray machine, were used in the study. The anatomical landmarks of both Steiner and McNamara analyses were manually traced using a third-party software AudaxCeph Empower, version 6.6.12.4731 (Audax d.o.o., Ljubljana, Slovenia), the tracing was performed by two radiologists with more than 5 years of experience in digital cephalometry to determine the inter-reliability, then it was repeated with an interval of two weeks to determine the intra-reliability. The landmarks were retraced automatically through the fully automatic option on the same software program using convolutional neural network.Results: Regarding McNamara analysis, the results of this study showed excellent reliability of the artificial intelligence measurements compared to the manual measurements, with an interclass correlation coefficient >0.9. Regarding Steiner analysis, our results showed excellent reliability of the artificial intelligence measurements compared to the manual measurements (0.75 |
| Databáze: | Directory of Open Access Journals |
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