OPGAgent: An Agent for Auditable Dental Panoramic X-ray Interpretation
Zhaolin Yu, Litao Yang, Ben Babicka, Ming Hu, Jing Hao, Anthony Huang, James Huang, Yueming Jin, Jiasong Wu, Zongyuan Ge

TL;DR
OPGAgent is a novel multi-tool agentic system designed for comprehensive, auditable interpretation of dental panoramic X-rays, outperforming existing vision language models and enabling detailed, structured clinical reporting.
Contribution
This work introduces OPGAgent, the first agentic system for dental X-ray analysis that combines specialized modules with a consensus mechanism, advancing accuracy and auditability in dental imaging interpretation.
Findings
Outperforms current dental VLMs on structured-report and VQA tasks.
Provides comprehensive, auditable analysis with conflict resolution.
Demonstrates effectiveness on OPG-Bench and MMOral-OPG benchmarks.
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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsDental Radiography and Imaging · Dental Research and COVID-19 · Multimodal Machine Learning Applications
