首个能同时检测胸部X光片变化并定位病灶的模型
TRACE: Temporal Radiology with Anatomical Change Explanation for Grounded X-ray Report Generation
- 联合时序对比与空间定位，生成变化描述
- 定位准确率超90%，可精准标注病灶变化
- 适合临床辅助诊断与医学影像研究者
胸片的时序对比是临床放射学的核心，有助于发现疾病进展、治疗反应及新发异常。尽管视觉-语言模型已推动单图报告生成与视觉定位的发展，但尚无方法能将二者结合用于时序变化检测。我们提出时空放射学分析模型TRACE，首次实现对前后两期胸片的联合时序对比、变化分类与空间定位。给定前序与当前胸片，TRACE可生成自然语言描述变化情况（恶化、改善、稳定），并用边界框坐标定位每个发现。实验显示其空间定位准确率超过90%，为该挑战性任务奠定基础。消融实验揭示：仅当时序对比与空间定位联合学习时，变化检测能力才会出现，单独使用任一模块均无法实现有效检测。这表明空间定位提供了时序推理所必需的空间注意力机制。
原文摘要 · Abstract (English)
Temporal comparison of chest X-rays is fundamental to clinical radiology, enabling detection of disease progression, treatment response, and new findings. While vision-language models have advanced single-image report generation and visual grounding, no existing method combines these capabilities for temporal change detection. We introduce Temporal Radiology with Anatomical Change Explanation (TRACE), the first model that jointly performs temporal comparison, change classification, and spatial localization. Given a prior and current chest X-ray, TRACE generates natural language descriptions of interval changes (worsened, improved, stable) while grounding each finding with bounding box coordinates. TRACE demonstrates effective spatial localization with over 90% grounding accuracy, establishing a foundation for this challenging new task. Our ablation study uncovers an emergent capability: change detection arises only when temporal comparison and spatial grounding are jointly learned, as neither alone enables meaningful change detection. This finding suggests that grounding provides a spatial attention mechanism essential for temporal reasoning.
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