Radiology Report Evaluation

Overview

The field develops ways to score report-generation and report-review systems for clinical accuracy, completeness, and harmful errors—not just similarity to a reference report. Approaches include finding-level extraction and matching, clinical graphs, question answering and entailment, severity-aware LLM judges, and direct radiologist review. Benchmarks span chest X-rays, CT, PET, MRI, and longitudinal reports, with growing attention to spatial grounding, report-writing conventions, and whether findings are supported by images. A central tension is that fluent reports and high text-overlap scores can conceal omissions or unsupported claims, while more clinically aligned metrics still need to be transparent, consistent, and validated across settings.

Latest papers

CardsList

32 papers4 papers in the last four weeks, down 33% on the four weeks before. 0.0% of all new papers.

  1. Standardizing Longitudinal Radiology Report Evaluation via Large Language Model Annotation

    Jan 23, 2026Xinyi Wang, Grazziela Figueredo, Ruizhe Li +1Medical Report GenerationLLM-Assisted Annotation