Lunguage：结构化与序列化胸部X光解读基准测试

摘要

放射学报告详细记录了临床观察结果，并捕捉了随时间演变的诊断推理过程。然而，现有的评估方法仅限于单份报告场景，且依赖于粗糙的指标，无法捕捉细粒度的临床语义和时间依赖性。我们推出了LUNGUAGE，一个用于结构化放射学报告生成的基准数据集，它支持单份报告评估和跨多次研究的纵向患者层面评估。该数据集包含1,473份经过专家审阅的胸部X光报告，其中80份包含纵向注释，以捕捉疾病进展和研究间间隔，这些注释同样经过专家审阅。利用这一基准，我们开发了一个两阶段框架，将生成的报告转化为细粒度、与模式对齐的结构化表示，从而实现纵向解读。我们还提出了LUNGUAGESCORE，一种可解释的评估指标，它在实体、关系和属性层面比较结构化输出，同时建模患者时间线上的时间一致性。这些贡献为序列放射学报告建立了首个基准数据集、结构化框架和评估指标，实证结果表明LUNGUAGESCORE有效支持了结构化报告评估。代码已公开于：https://github.com/SuperSupermoon/Lunguage。

English

Radiology reports convey detailed clinical observations and capture diagnostic reasoning that evolves over time. However, existing evaluation methods are limited to single-report settings and rely on coarse metrics that fail to capture fine-grained clinical semantics and temporal dependencies. We introduce LUNGUAGE,a benchmark dataset for structured radiology report generation that supports both single-report evaluation and longitudinal patient-level assessment across multiple studies. It contains 1,473 annotated chest X-ray reports, each reviewed by experts, and 80 of them contain longitudinal annotations to capture disease progression and inter-study intervals, also reviewed by experts. Using this benchmark, we develop a two-stage framework that transforms generated reports into fine-grained, schema-aligned structured representations, enabling longitudinal interpretation. We also propose LUNGUAGESCORE, an interpretable metric that compares structured outputs at the entity, relation, and attribute level while modeling temporal consistency across patient timelines. These contributions establish the first benchmark dataset, structuring framework, and evaluation metric for sequential radiology reporting, with empirical results demonstrating that LUNGUAGESCORE effectively supports structured report evaluation. The code is available at: https://github.com/SuperSupermoon/Lunguage

Lunguage：结构化与序列化胸部X光解读基准测试

Lunguage: A Benchmark for Structured and Sequential Chest X-ray Interpretation

摘要

Summary

Support

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