Developing Synthetic Orthopantomogram Datasets Through Generative Models

Inability to differentiate synthetic OPGs highlights the realism of the generated images, suggesting their high quality. The authors propose using diffusion models to create annotated synthetic datasets for diverse AI training in healthcare diagnostics.

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Publication Details

Journal
International Dental Journal
Published
2026-03-13
DOI
https://doi.org/10.1016/j.identj.2026.109465
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Developing Synthetic Orthopantomogram Datasets Through Generative Models

Fahad Umer, Niha Adnan, Syed Muhammad Faizan Ahmed
International Dental Journal
Machine Learning in Healthcare
article

Developing Synthetic Orthopantomogram Datasets Through Generative Models

Fahad Umer, Niha Adnan, Syed Muhammad Faizan Ahmed
article en

Abstract

Inability to differentiate synthetic OPGs highlights the realism of the generated images, suggesting their high quality. The authors propose using diffusion models to create annotated synthetic datasets for diverse AI training in healthcare diagnostics.

International Dental JournalVol. 76(3)
Aga Khan University Hospital (PK)
Industry, innovation and infrastructure
Openalex Percentile: Top 29%
Machine Learning in Healthcare
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