ArticleScientific reports2025
Optimizing dental implant identification using deep learning leveraging artificial data.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The trial behind it
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Who cites it
4 citing papers in PubMed.
- Deep Learning-Based Identification of Dental Implant Systems from Two-Dimensional Radiographs.Diagnostics (Basel, Switzerland) · 2026Article
- Multi-Class Malocclusion Detection on Standardized Intraoral Photographs Using YOLOv11.Dentistry journal · 2026Article
- Optimized classification of dental implants using convolutional neural networks and pre-trained models with preprocessed data.BMC oral health · 2025Article
- Comparing Manual and ChatGPT Deep Research on Systematic Search and Selection in the PubMed Database on the Topic of Dental Implantology.International journal of dentistry · 2025Article
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aims to evaluate the potential enhancement in implant classification performance achieved by incorporating artificially generated images of commercially available products into a deep learning process of dental implant classification using panoramic X-ray images. To supplement an existing dataset of 7,946 in vivo dental implant images, a three-dimensional scanner was employed to create implant surface models. Subsequently, implant surface models were used to generate two-dimensional X-ray images, which were compiled along with original images to create a comprehensive dataset. Images of 10 types of implants were classified using ResNet50 into the following datasets: (A) images of implants captured in vivo, (B) artificial implant images generated without background adjustments, and (C) implant images derived from in vivo images and generated with background adjustments. The classification accuracy was 0.8888 for dataset A, 0.903 for dataset B, and 0.9146 for dataset C. Notably, dataset C demonstrated the highest performance and exhibited the optimal feature distribution. In the context of deep learning classifiers for dental implants using panoramic X-ray images, incorporating artificially generated X-ray images-designed to mirror the appearance of human body implants-proved to be the most beneficial in enhancing the performance of the classification model.
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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.