用智能体系统提升牙科全景片分析的准确性与可审计性
OPGAgent: An Agent for Auditable Dental Panoramic X-ray Interpretation
- 分阶段调用专用工具，动态解析全景片全局、象限和牙齿层级信息
- 在双数据集上超越现有牙科视觉语言模型与医疗智能体框架
- 支持临床报告级审查，可检测幻觉并验证诊断结果可靠性
正颌全景片（OPG）是牙科全牙列筛查的标准影像，广泛用于多种诊断任务。尽管视觉语言模型（VLMs）可通过自然语言实现多任务分析，但在多数具体任务上仍逊于专用模型。通过协调专用工具的智能体系统，有望兼顾灵活性与精度，但该方法在牙科影像领域尚未探索。为此，我们提出OPGAgent，一种可审计的多工具智能体系统，用于全景片解读。其包含三部分：（1）分层证据收集模块，将分析分解为全局、象限和牙齿层级，并动态调用工具；（2）专用工具箱，集成空间、检测、功能与专家知识库；（3）共识子代理，利用解剖约束解决冲突。我们还提出OPG-Bench，基于真实临床报告构建的结构化报告协议，采用（位置、领域、值）三元组形式，实现对发现与幻觉的全面评估，突破传统VQA指标局限。在自建的OPG-Bench与公开的MMOral-OPG基准上，OPGAgent在结构化报告与VQA评价中均优于当前牙科VLM与医学智能体框架。代码将在录用后开源。
原文摘要 · Abstract (English)
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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