ArticleBioengineering (Basel, Switzerland)2023
Improving Dental Implant Outcomes: CNN-Based System Accurately Measures Degree of Peri-Implantitis Damage on Periapical Film.
Article in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 2 syntheses or guidelines pooled it, 40 citations in OpenAlex.
- Diagnostic performance of artificial intelligence in periapical radiography: a systematic review.Odontology · 2026Pooled it
- Diagnostic Accuracy of Deep Learning Models in Detecting Peri-Implant Marginal Bone Loss: A Systematic Review and Meta-Analysis.Clinical oral implants research · 2026Pooled it
- Artificial Intelligence for Radiographic Diagnosis of Peri-Implantitis: A Comprehensive Review on Detection, Measurement, and Risk Stratification.Journal of clinical medicine · 2026Review
- AI detection of peri-implantitis on 2D radiographs: a systematic review and diagnostic accuracy assessment.Odontology · 2026Review
- Detection and Classification of Peri-Implant Marginal Bone Loss in Cone-Beam Computed Tomography Using a Deep Learning Approach.Clinical and experimental dental research · 2026Article
- A web-based deep learning cascade for automated detection and quantification of marginal bone loss.BMC oral health · 2026Article
- Fractal Analysis and Artificial Intelligence for Radiographic Detection of Periodontal Bone Loss: A Systematic Review.Diagnostics (Basel, Switzerland) · 2026Review
- Dental Implantation Changes the Bone Morphology and Mineral Density of Human Mandibular Condyle: A Pilot Study.Journal of functional biomaterials · 2026Article
- A Deep Metric Learning and Multimodal Gated Fusion Framework for AI-Driven Risk Assessment of Lingual Plate Perforation and Mandibular Canal Injury in Posterior Mandible Implants.International journal of dentistry · 2026Article
- Automated assessment of peri-implant disease severity by deep learning and image processing in periapical radiographs.Journal of dental sciences · 2026Article
- Short-Term Administration of Parathyroid Hormone Improves Wound Healing Around Implants in an Osteoporotic Rat Model.Journal of clinical medicine · 2025Article
- Accuracy in diagnosing caries in young permanent molars using interproximal radiographic imaging and validation by artificial intelligence.Journal of clinical and experimental dentistry · 2025Article
- Deep Learning-Assisted Diagnostic System: Implant Brand Detection Using Improved IB-YOLOv10 in Periapical Radiographs.Diagnostics (Basel, Switzerland) · 2025Article
- Accuracy of Artificial Intelligence Models in Detecting Peri-Implant Bone Loss: A Systematic Review.Diagnostics (Basel, Switzerland) · 2025Review
- Precision Medicine Assessment of the Radiographic Defect Angle of the Intrabony Defect in Periodontal Lesions by Deep Learning of Bitewing Radiographs.Bioengineering (Basel, Switzerland) · 2025Article
- Applications of Machine Learning in Periodontology and Implantology: A Comprehensive Review.Annals of biomedical engineering · 2024Review
- Precision Medicine for Apical Lesions and Peri-Endo Combined Lesions Based on Transfer Learning Using Periapical Radiographs.Bioengineering (Basel, Switzerland) · 2024Article
- Evaluation of the Alveolar Crest and Cemento-Enamel Junction in Periodontitis Using Object Detection on Periapical Radiographs.Diagnostics (Basel, Switzerland) · 2024Article
- DeMambaNet: Deformable Convolution and Mamba Integration Network for High-Precision Segmentation of Ambiguously Defined Dental Radicular Boundaries.Sensors (Basel, Switzerland) · 2024Article
- Auxiliary Diagnosis of Dental Calculus Based on Deep Learning and Image Enhancement by Bitewing Radiographs.Bioengineering (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
13 authors at 6 institutions in 3 countries.
Funding
Abstract
As the popularity of dental implants continues to grow at a rate of about 14% per year, so do the risks associated with the procedure. Complications such as sinusitis and nerve damage are not uncommon, and inadequate cleaning can lead to peri-implantitis around the implant, jeopardizing its stability and potentially necessitating retreatment. To address this issue, this research proposes a new system for evaluating the degree of periodontal damage around implants using Periapical film (PA). The system utilizes two Convolutional Neural Networks (CNN) models to accurately detect the location of the implant and assess the extent of damage caused by peri-implantitis. One of the CNN models is designed to determine the location of the implant in the PA with an accuracy of up to 89.31%, while the other model is responsible for assessing the degree of Peri-implantitis damage around the implant, achieving an accuracy of 90.45%. The system combines image cropping based on position information obtained from the first CNN with image enhancement techniques such as Histogram Equalization and Adaptive Histogram Equalization (AHE) to improve the visibility of the implant and gums. The result is a more accurate assessment of whether peri-implantitis has eroded to the first thread, a critical indicator of implant stability. To ensure the ethical and regulatory standards of our research, this proposal has been certified by the Institutional Review Board (IRB) under number 202102023B0C503. With no existing technology to evaluate Peri-implantitis damage around dental implants, this CNN-based system has the potential to revolutionize implant dentistry and improve patient outcomes.
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What OpenQuestion holds
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.