OralGPT-Plus：通过强化学习学习使用视觉工具进行全景X射线分析
OralGPT-Plus: Learning to Use Visual Tools via Reinforcement Learning for Panoramic X-ray Analysis
AI总结：
OralGPT-Plus通过强化学习实现全景X射线分析中的交互式对称推理，提升诊断可靠性。
摘要：
全景牙科X射线图像需要精细的空间推理、双侧对称性理解以及多步骤的诊断验证，但现有的视觉-语言模型采用静态单次通过范式，限制了其临床可靠性。在本文中，我们引入了OralGPT-Plus，一种代理视觉-语言模型，旨在进行迭代性和对称性感知的诊断推理，用于全景牙科X射线图像分析。为了支持这一范式，我们构建了DentalProbe，一个包含五千张图像的数据集，其中包含专家编纂的诊断轨迹，为局部检查和对侧比较提供结构化监督。我们进一步开发了一种重检驱动的强化学习框架，该框架鼓励具有临床意义的重新检查，并通过基于评分的奖励和条件诊断驱动奖励来稳定长周期推理。同时，我们提出了MMOral-X，首个全面的全景诊断基准，包含300个开放性问题和区域级注释，涵盖多个难度级别。OralGPT-Plus在MMOral-X和已建立的全景基准上显示出一致且可靠的改进，表明了交互性和对称性感知推理的有效性。我们的工作强调了代理建模在牙科成像中的价值，并为未来在临床对齐的全景X射线分析中的研究提供了基础。
英文摘要：
Panoramic dental radiographs require fine-grained spatial reasoning, bilateral symmetry understanding, and multi-step diagnostic verification, yet existing vision-language models operate under a static single-pass paradigm that limits their clinical reliability. In this paper, we introduce OralGPT-Plus, an agentic vision-language model designed to perform iterative and symmetry-aware diagnostic reasoning for panoramic dental radiograph analysis. To support this paradigm, we construct DentalProbe, a five-thousand-image dataset with expert-curated diagnostic trajectories that provide structured supervision for localized inspection and contralateral comparison. We further develop a Reinspection-driven reinforcement learning framework that encourages clinically meaningful re-examination and stabilizes long-horizon reasoning with rubric-based reward and conditioned diagnostic-driven reward. In parallel, we present MMOral-X, the first benchmark for holistic panoramic diagnosis, containing 300 open-ended questions and region-level annotations across multiple difficulty levels. OralGPT-Plus demonstrates consistent and reliable improvements over strong baselines on MMOral-X and established panoramic benchmarks, indicating the effectiveness of interactive and symmetry-informed reasoning. Our work highlights the value of agentic modeling for dental imaging and provides a foundation for future research in clinically aligned panoramic radiograph analysis.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
