ArticleJournal of clinical medicine2022
Comparing a Fully Automated Cephalometric Tracing Method to a Manual Tracing Method for Orthodontic Diagnosis.
Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
21 citing papers in PubMed, 43 citations in OpenAlex.
- Comparison of W. Arnett's cephalometric analysis measurements performed using artificial intelligence and manual measurements.Clinical oral investigations · 2026Article
- Comparison of cervical vertebrae morphology in individuals with different growth patterns: An observational study.Journal of orthodontic science · 2026Article
- Evaluating a cost-effective, web-based AI platform for lateral cephalometric analysis: a comparative in-silico study.BMC oral health · 2025Article
- Applications of artificial intelligence in diagnosis and treatment planning of orthodontics: a narrative review.The Saudi dental journal · 2025Review
- Growth Prediction in Orthodontics: ASystematic Review of Past Methods up to Artificial Intelligence.Children (Basel, Switzerland) · 2025Review
- AI-Driven Advancements in Orthodontics for Precision and Patient Outcomes.Dentistry journal · 2025Review
- Applications of Artificial Intelligence in Dental Medicine: A Critical Review.International dental journal · 2025Review
- Automatic detection and proximity quantification of inferior alveolar nerve and mandibular third molar on cone-beam computed tomography.Clinical oral investigations · 2024Article
- Reliability and accuracy of Artificial intelligence-based software for cephalometric diagnosis. A diagnostic study.BMC oral health · 2024Article
- Comparison of Three Commercially Available, AI-Driven Cephalometric Analysis Tools in Orthodontics.Journal of clinical medicine · 2024Article
- A Comparative Analysis of Artificial Intelligence and Manual Methods for Three-Dimensional Anatomical Landmark Identification in Dentofacial Treatment Planning.Bioengineering (Basel, Switzerland) · 2024Article
- A comparative evaluation of concordance and speed between smartphone app-based and artificial intelligence web-based cephalometric tracing software with the manual tracing method: A cross-sectional study.Journal of clinical and experimental dentistry · 2024Article
- Artificial Intelligence and Its Clinical Applications in Orthodontics: A Systematic Review.Diagnostics (Basel, Switzerland) · 2023Review
- The Evolution of Robin Sequence Treatment Based on the Biomimetic Interdisciplinary Approach: A Historical Review.Biomimetics (Basel, Switzerland) · 2023Review
- Skull Biomechanics and Simplified Cephalometric Lines for the Estimation of Muscular Lines of Action.Journal of personalized medicine · 2023Article
- Correlation Analysis of Nasal Septum Deviation and Results of AI-Driven Automated 3D Cephalometric Analysis.Journal of clinical medicine · 2023Article
- Application of Artificial Intelligence in Orthodontics: Current State and Future Perspectives.Healthcare (Basel, Switzerland) · 2023Review
- Application of Artificial Intelligence (AI) in a Cephalometric Analysis: A Narrative Review.Diagnostics (Basel, Switzerland) · 2023Review
- Review
- Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment.Healthcare (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study aims to compare an automated cephalometric analysis based on the latest deep learning method of automatically identifying cephalometric landmarks with a manual tracing method using broadly accepted cephalometric software. Methods: A total of 100 cephalometric X-rays taken using a CS8100SC cephalostat were collected from a private practice. The X-rays were taken in maximum image size (18 × 24 cm lateral image). All cephalometric X-rays were first manually traced using the Dolphin 3D Imaging program version 11.0 and then automatically, using the Artificial Intelligence CS imaging V8 software. The American Board of Orthodontics analysis and the European Board of Orthodontics analysis were used for the cephalometric measurements. This resulted in the identification of 16 cephalometric landmarks, used for 16 angular and 2 linear measurements. Results: All measurements showed great reproducibility with high intra-class reliability (>0.97). The two methods showed great agreement, with an ICC range of 0.70−0.92. Mean values of SNA, SNB, ANB, SN-MP, U1-SN, L1-NB, SNPg, ANPg, SN/ANS-PNS, SN/GoGn, U1/ANS-PNS, L1-APg, U1-NA, and L1-GoGn landmarks had no significant differences between the two methods (p > 0.0027), while the mean values of FMA, L1-MP, ANS-PNS/GoGn, and U1-L1 were statistically significantly different (p < 0.0027). Conclusions: The automatic cephalometric tracing method using CS imaging V8 software is reliable and accurate for all cephalometric measurements.
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Registered trials
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.