AI-ASSISTED CEPHALOMETRIC ANALYSIS VERSUS MANUAL TRACING: A LITERATURE REVIEW
DOI:
https://doi.org/10.31435/ijitss.3(51).2026.6342Keywords:
Artificial Intelligence, Orthodontists, Cephalometric Analysis, Landmark Detection, ComparisonAbstract
Objectives: This review aimed to investigate the accuracy, agreement, and repeatability of artificial intelligence driven cephalometric analysis compared with conventional manual tracing performed by orthodontic experts.
Methods: A structured literature review was conducted using the PubMed database. The search was performed on May 5, 2026, and included English-language studies published within the previous five years. Studies evaluating the accuracy and reliability of AI-based cephalometric landmark identification and/or cephalometric measurements compared with manual tracing were considered eligible. Meta-analyses, systematic reviews, umbrella reviews, critical reviews, and high-quality comparative studies were included. Of the 113 records identified, 30 full-text articles were assessed for eligibility, and 17 studies met the inclusion criteria and were included in the final review.
Results: AI-assisted cephalometric analysis demonstrated high agreement with manual landmark identification performed by experienced orthodontists across the reviewed studies. Contemporary deep learning algorithms achieved clinically acceptable accuracy for most routinely used cephalometric landmarks and markedly reduced analysis time compared with conventional manual tracing. Nevertheless, discrepancies persisted for anatomically challenging landmarks, and all reviewed studies recommended clinician verification of AI-generated analyses.
Conclusions: AI‑driven cephalometric analysis provides clinically comparable accuracy to manual tracing and offers enhanced consistency and efficiency. While AI cannot yet replace orthodontists in complex diagnostic scenarios, it serves as a reliable and effective complementary tool for routine cephalometric assessment.
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Copyright (c) 2026 Agnieszka Ciepiela, Gabriela Pilch, Malgorzata Berowska, Jakub Sagan, Michal Zemowski, Zuzanna Kucia, Daniil Yefimchuk
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