What question did this study set out to answer?

The aim is to evaluate a hybrid AI framework for identifying implant brands and classifying degrees of bone loss using radiographs.

June 21, 2026Journal of the Formosan Medical AssociationOpen Access

Automated detection of marginal bone loss levels in implant brands using deep learning on periapical radiographs

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Authors

YSYuning SuTaoyuan Chang Gung Memorial Hospital CCChiung-An ChenMing Chi University of Technology LCLi‐Hsin ChangChung Yuan Christian University

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Implication

Randomized trial evaluates an AI framework for detecting bone loss in different implant brands, suggesting improved diagnostic accuracy and efficiency.

Key Points

The aim is to evaluate a hybrid AI framework for identifying implant brands and classifying degrees of bone loss using radiographs.
Analyzed 708 periapical radiographs featuring 3i and Xive implants using a YOLOv8 model for implant localization.
Employed a custom segmentation algorithm and a two-stage clustering method for alveolar crest detection.
Implemented EfficientNet-B3 for multi-task classification across 12 composite categories.
YOLOv8 model achieved 99.39% precision and 98.63% sensitivity.
The system's overall accuracy in complex classification reached 97.42%, with 98.28% for specific Xive/Prothesis/Diseased category.
Average assessment time reduced from 15.5 seconds to 0.16 seconds, while diagnostic accuracy improved from 90.73% to 97.38%.

Cite This Study

Su et al. (2026) studied this question.

synapsesocial.com/papers/6a377f3a24f042ddf4c59db3 https://doi.org/10.1016/j.jfma.2026.06.011

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Implication

Randomized trial evaluates an AI framework for detecting bone loss in different implant brands, suggesting improved diagnostic accuracy and efficiency.

Automated detection of marginal bone loss levels in implant brands using deep learning on periapical radiographs

Discussion

Member takes

Implication

Key Points

Cite This Study

Automated detection of marginal bone loss levels in implant brands using deep learning on periapical radiographs

Discussion

Member takes

Implication

Key Points

Cite This Study

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