Evaluating the Accuracy of Automated Cephalometric Analysis Based on Artificial Intelligence
Main Article Content
Abstract
Objective: To determine the correlation and comparison between artificial intelligence (AI) cephalometric tracing and manual human tracing of cephalograms.
Methodology: This cross sectional comparative study was conducted on cephalograms from 100 participants at Saidu College of Dentistry, Swat, using a non-probability sampling technique. Informed consent was not required as the study utilized existing radiographic records with prior patient consent. Age and gender were documented, followed by the manual tracing of 100 cephalograms by a sole operator, which were subsequently analyzed using AudaxCeph software. Pearson correlation testing and paired t-tests were utilized for analysis.
Results: The participants' average age was 19.39 years (SD ± 6.24), with a gender distribution of 56% female and 44% male. The results revealed strong positive correlations (0.91 to 0.98) between manually and software-traced cephalometric parameters, with statistically significant p-values (<0.01). Paired t-tests showed no significant differences across various parameters, affirming the reliability of the software-generated cephalometric measurements.
Conclusion: This research showcases the precision of the software in evaluating distinct cephalometric measurements, emphasizing its promise as a dependable instrument for orthodontic diagnosis and planning treatments.
Article Details
Work published in JPMI is licensed under a
Creative Commons Attribution-NonCommercial 2.0 Generic License.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
References
Jiang F, Guo Y, Yang C, Zhou Y, Lin Y, Cheng F, et al. Artificial intelligence system for automated landmark localization and analysis of cephalometry. Dentomaxillofac Radiol 2023;52(1):20220081.
Yao J, Zeng W, He T, Zhou S, Zhang Y, Guo J, et al. Automatic localization of cephalometric landmarks based on convolutional neural network. Am J Orthod Dentofacial Orthop 2022;161(3):e250-9.
Kietczykowski M, Kaminski K, Perkowski K, Zadurska M, Czochrowska E. Application of artificial intelligence (AI) in a cephalometric analysis: a narrative review. Diagnostics 2023;13(16):2640.
Hendrickx J, Gracea RS, Vanheers M, Winderickx N, Preda F, Shujaat S, et al. Can artificial intelligence-driven cephalometric analysis replace manual tracing? A systematic review and meta-analysis. Eur J Orthod 2024;46(4):cjae029.
Ribas-Sabartes J, Sanchez-Molins M, d’Oliveira NG. The accuracy of algorithms used by artificial intelligence in cephalometric points detection: a systematic review. Bioengineer 2024;11(12):1286.
Ristau B, Coreil M, Chapple A, Armbruster P, Ballard R. Comparison of AudaxCeph®’s fully automated cephalometric tracing technology to a semi-automated approach by human examiners. Int Orthod 2022;20(4):100691.
Mahto RK, Kafle D, Giri A, Luintel S, Karki A. Evaluation of fully automated cephalometric measurements obtained from web-based artificial intelligence driven platform. BMC Oral Health 2022;22(1):132.
Mahto RK, Kafle D, Giri A, Luintel S, Karki A. Evaluation of fully automated cephalometric measurements obtained from web-based artificial intelligence driven platform. BMC Oral Health 2022;22(1):1-8.
Danisman H. Artificial intelligence web-based cephalometric analysis platform: comparison with the computer assisted cephalometric method. Clin Investig Orthod 2023;82(4):194-203.
Bor S, Cigerim SC, Kotan S. Comparison of AI-assisted cephalometric analysis and orthodontist-performed digital tracing analysis. Prog Orthod 2024;25(1):41.
Kunz F, Stellzig-Eisenhauer A, Widmaier LM, Zeman F, Boldt J. Assessment of the quality of different commercial providers using artificial intelligence for automated cephalometric analysis compared to human orthodontic experts. J Orofac Orthop 2023;23:1-16.