  Radiology report summarization (RRS) is a growing area of research. Given the
Findings section of a radiology report, the goal is to generate a summary
(called an Impression section) that highlights the key observations and
conclusions of the radiology study. However, RRS currently faces essential
limitations.First, many prior studies conduct experiments on private datasets,
preventing reproduction of results and fair comparisons across different
systems and solutions. Second, most prior approaches are evaluated solely on
chest X-rays. To address these limitations, we propose a dataset (MIMIC-RRS)
involving three new modalities and seven new anatomies based on the MIMIC-III
and MIMIC-CXR datasets. We then conduct extensive experiments to evaluate the
performance of models both within and across modality-anatomy pairs in
MIMIC-RRS. In addition, we evaluate their clinical efficacy via RadGraph, a
factual correctness metric.
