ArticleDiagnostics (Basel, Switzerland)2023
Automatic Segmentation of Teeth, Crown-Bridge Restorations, Dental Implants, Restorative Fillings, Dental Caries, Residual Roots, and Root Canal Fillings on Orthopantomographs: Convenience and Pitfalls.
Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- EGT-UNet: Evolutionary Game-Theoretic Adaptive Optimization for Pediatric Panoramic Tooth Segmentation.Bioengineering (Basel, Switzerland) · 2026Article
- Comparison of linear and angular cephalometric measurements in CBCT using semi-automated software and artificial intelligence-generated cephalograms.BMC oral health · 2026Article
- Automated differentiation of caries requiring filling and caries necessitating root canal treatment using machine learning.Oral radiology · 2026Article
- Evaluation of Root Angulations Through Panoramic Films Using Artificial Intelligence.Diagnostics (Basel, Switzerland) · 2026Article
- A deep learning based automated maxillary sinus segmentation and bone grafts analysis in CBCT images.NPJ digital medicine · 2025Article
- Computational Insights into Root Canal Treatment: A Survey of Selected Methods in Imaging, Segmentation, Morphological Analysis, and Clinical Management.Dentistry journal · 2025Review
- Applications of Artificial Intelligence (AI) for Diagnosis of Periodontal/Peri-Implant Diseases: A Narrative Review.Journal of oral rehabilitation · 2025Review
- PXseg: automatic tooth segmentation, numbering and abnormal morphology detection based on CBCT and panoramic radiographs.BMC oral health · 2025Article
- Deep Learning-Based Detection of Separated Root Canal Instruments in Panoramic Radiographs Using a UDiagnostics (Basel, Switzerland) · 2025Article
- Role of Artificial Intelligence and Machine Learning in Conservative Dentistry and Endodontics: A Review.Cureus · 2025Review
- Artificial Intelligence Methods in the Detection of Oral Diseases on Pantomographic Images-A Systematic Narrative Review.Journal of clinical medicine · 2025Review
- Artificial intelligence (AI) in restorative dentistry: current trends and future prospects.BMC oral health · 2025Review
- DMAF-Net: deformable multi-scale adaptive fusion network for dental structure detection with panoramic radiographs.Dento maxillo facial radiology · 2024Article
- Combining public datasets for automated tooth assessment in panoramic radiographs.BMC oral health · 2024Article
- SEM Evaluation of Marginal Adaptation E-Max Crowns Manufactured by Printing-Pressed and Milling.Diagnostics (Basel, Switzerland) · 2023Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe aim of our study is to provide successful automatic segmentation of various objects on orthopantomographs (OPGs).
methods8138 OPGs obtained from the archives of the Department of Dentomaxillofacial Radiology were included. OPGs were converted into PNGs and transferred to the segmentation tool's database. All teeth, crown-bridge restorations, dental implants, composite-amalgam fillings, dental caries, residual roots, and root canal fillings were manually segmented by two experts with the manual drawing semantic segmentation technique.
resultsThe intra-class correlation coefficient (ICC) for both inter- and intra-observers for manual segmentation was excellent (ICC > 0.75). The intra-observer ICC was found to be 0.994, while the inter-observer reliability was 0.989. No significant difference was detected amongst observers (
conclusionsThanks to faster and automated diagnoses on 2D as well as 3D dental images, dentists will have higher diagnosis rates in a shorter time even without excluding cases.
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