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Application of deep learning in teeth identification tasks on panoramic radiographs
Fahad Umer1, Saqib Habib1, Niha Adnan1
1Operative Dentistry and Endodontics, Aga Khan University Hospital, Karachi, Sindh, Pakistan.
Dento Maxillo Facial Radiology
|February 10, 2022
Summary
Artificial Intelligence (AI) shows promise in identifying teeth on Panoramic Radiographs (PR). Deep Learning (DL) models demonstrate encouraging results, but future research must address identified limitations in AI teeth identification.
Area of Science:
- Dentistry
- Radiology
- Artificial Intelligence
Background:
- Panoramic Radiographs (PR) are crucial for dental diagnostics.
- Accurate teeth identification on PR is essential for treatment planning.
- Current advancements in Artificial Intelligence (AI) offer potential for automated analysis.
Purpose of the Study:
- To systematically review and evaluate the performance of Deep Learning (DL) models for teeth identification on PR.
- To compare the diagnostic performance of various DL models applied to this task.
Main Methods:
- A systematic review of studies using DL models for teeth identification on PR.
- Searches conducted across major medical and dental databases (PubMed NLM, EBSCO, Wiley Cochrane, IEEE Xplore).
- Risk of bias assessed using the modified QUADAS-2 tool; meta-analysis precluded by data heterogeneity.
Main Results:
- 13 relevant studies were included from an initial search of 282 articles.
- Diverse DL models were employed, reporting performance using varied metrics.
- No meta-analysis was possible due to heterogeneity in reported outcomes.
Conclusions:
- DL models show encouraging performance in teeth identification on PR.
- Identified shortcomings require further investigation and improvement by future research.
- AI-driven teeth identification on PR holds significant potential for dentistry.
