Evidence map›Paper›PMID 42154885›Full record

ArticleDental press journal of orthodontics2026

Accuracy of cephalometric landmark identification on artificial intelligence-based software: a comparative study.

İpek Şavkan, Sara Nur Özçankaya, Öykü Naz Turan

Abstract readComparative Study
In one paragraph

Article in Dental press journal of orthodontics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

İpek Şavkanİstanbul Kent University, Faculty of Dentistry, Department of Orthodontics (Istanbul, Türkiye).ORCID http://orcid.org/0000-0002-8144-1320
Sara Nur Özçankayaİstanbul Kent University, Faculty of Dentistry, Department of Orthodontics (Istanbul, Türkiye).ORCID http://orcid.org/0009-0002-6393-7215
Öykü Naz TuranIstanbul University, Faculty of Dentistry, Department of Orthodontics (Istanbul, Türkiye).ORCID http://orcid.org/0009-0009-7668-9960

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCephalometry has long been a cornerstone of orthodontic diagnosis and treatment planning. While traditionally performed manually, cephalometric analysis has increasingly shifted toward semi-automated or fully automated computer-based software, due to advances in technology.

objectiveThis study aims to evaluate and compare the accuracy of anatomical landmarks identified manually by orthodontists using digital tools versus those identified automatically by various artificial intelligence (AI)-based cephalometric software.

methodsA total of 25 lateral cephalometric radiographs were selected for analysis. Manual landmark identification was independently performed by two orthodontists using the digital cephalometric software NemoCeph. These were compared to the automatic landmark identifications generated by two AI-based programs: CephNinja and WebCeph™. A total of 17 anatomical landmarks, 15 hard tissue and 2 soft tissue points, were evaluated. The 17 cephalometric landmarks selected in this study are among the most commonly used and reliably identifiable reference points in the literature. To facilitate direct visual comparison, landmark positions derived from all three methods were overlaid using semi-transparent image layers. One-way ANOVA and intraclass correlation coefficient (ICC) tests were conducted to assess inter-method differences. The threshold for statistical significance was set at p < 0.05 and p < 0.01.

resultsStatistically significant differences were observed at the porion, basion, gonion, and the apexes of the upper and lower incisors (p < 0.05). Compared to the manual tracings in NemoCeph, AI-based software generally placed these landmarks in more distal and superior positions. Among the AI tools, CephNinja showed greater similarity to NemoCeph for the gonion and basion points, while WebCeph™ was closer at the incisor apexes.

conclusionAlthough AI-based cephalometric software offers rapid and reproducible assessments, certain anatomical landmarks - particularly porion, basion, gonion, and the apexes of the upper and lower incisors - demonstrate statistically significant positional discrepancies, compared to manual tracings. Clinicians should be cautious when relying exclusively on automated analyses for diagnostic or treatment planning purposes, since AI struggles with certain landmarks, due to algorithmic limitations.

Indexed as

Anatomic LandmarksArtificial IntelligenceCephalometryImage Processing, Computer-AssistedSoftwareHumans

Identifiers

PMID42154885
PMCPMC13185511

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.