OPGAgent: An Agent for Auditable Dental Panoramic X-ray Interpretation

Zhaolin Yu, Litao Yang, Ben Babicka, Ming Hu, Jing Hao +5 more
2/28/2026
cs.CVcs.AI

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Abstract

Orthopantomograms (OPGs) are the standard panoramic radiograph in dentistry, used for full-arch screening across multiple diagnostic tasks. While Vision Language Models (VLMs) now allow multi-task OPG analysis through natural language, they underperform task-specific models on most individual tasks. Agentic systems that orchestrate specialized tools offer a path to both versatility and accuracy, this approach remains unexplored in the field of dental imaging. To address this gap, we propose OPGAgent, a multi-tool agentic system for auditable OPG interpretation. OPGAgent coordinates specialized perception modules with a consensus mechanism through three components: (1) a Hierarchical Evidence Gathering module that decomposes OPG analysis into global, quadrant, and tooth-level phases with dynamically invoking tools, (2) a Specialized Toolbox encapsulating spatial, detection, utility, and expert zoos, and (3) a Consensus Subagent that resolves conflicts through anatomical constraints. We further propose OPG-Bench, a structured-report protocol based on (Location, Field, Value) triples derived from real clinical reports, which enables a comprehensive review of findings and hallucinations, extending beyond the limitations of VQA indicators. On our OPG-Bench and the public MMOral-OPG benchmark, OPGAgent outperforms current dental VLMs and medical agent frameworks across both structured-report and VQA evaluation. Code will be released upon acceptance.

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Cite this paper

@article{yu2026opgagent,
  title  = {OPGAgent: An Agent for Auditable Dental Panoramic X-ray Interpretation},
  author = {Zhaolin Yu and Litao Yang and Ben Babicka and Ming Hu and Jing Hao and Anthony Huang and James Huang and Yueming Jin and Jiasong Wu and Zongyuan Ge},
  year   = {2026},
  eprint = {2603.00462},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2603.00462v1}
}

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