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CXRGraph: Using Information Extraction to Normalize the Training Data for Automatic Radiology Report Generation

Yuxiang Liao, Hoisang Heung, Hantao Liu, et al.

CXRGraph is a structured radiology report dataset built upon RadGraph and tailored for the Automatic Radiology Report Generation task. It can identify more task-relevant information such as abnormalities and hallucinated prior references.

relation extraction information extraction natural language processing named entity recognition structured radiology report

Published: Feb. 3, 2025. Version: 1.0.0

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RadGraph-XL: A Large-Scale Expert-Annotated Dataset for Entity and Relation Extraction from Radiology Reports

Jean-Benoit Delbrouck

RadGraph-XL is a large, expert-annotated dataset of 2,300 radiology reports covering multiple modalities and anatomies. It enables accurate extraction of clinical entities and relations for downstream medical AI tasks.

Published: Sept. 12, 2025. Version: 1.0.0

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RadGraph: Extracting Clinical Entities and Relations from Radiology Reports

Saahil Jain, Ashwin Agrawal, Adriel Saporta, et al.

RadGraph is a dataset of entities and relations in full-text chest X-ray radiology reports, which are obtained using a novel information extraction (IE) schema to capture clinically relevant information in a radiology report.

entity and relation extraction graph multi-modal natural language processing radiology

Published: June 3, 2021. Version: 1.0.0

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

Jong Hak Moon, Geon Choi, Paloma Rabaey, et al.

A radiologist-annotated benchmark of structured chest X-ray reports at single and sequential levels, comprising 1,473 reports across 18 relation types and 80 longitudinal cases.

fine-grained structured reports attribute-level clinical reasoning medical text structuring longitudinal clinical reasoning chest x-ray report parsing medical information structuring benchmark dataset for radiology report medical information extraction structured radiology reports temporal relation extraction radiology report benchmarking longitudinal clinical understanding

Published: Jan. 11, 2026. Version: 1.0.0

Database Credentialed Access

MIMIC-CXR-JPG - chest radiographs with structured labels

Alistair Johnson, Matthew Lungren, Yifan Peng, et al.

Chest x-rays in JPG format with structured labels derived from the associated radiology report.

computer vision chest x-ray radiology deep learning mimic

Published: March 12, 2024. Version: 2.1.0

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Pulmonary Edema Severity Grades Based on MIMIC-CXR

Ruizhi Liao, Geeticka Chauhan, Polina Golland, et al.

Pulmonary edema metadata and labels for MIMIC-CXR

Published: Feb. 9, 2021. Version: 1.0.1

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Application of Med-PaLM 2 in the refinement of MIMIC-CXR labels

Kendall Park, Rory Sayres, Andrew Sellergren, et al.

This work further refines the labels associated with CheXpert in MIMIC-CXR-JPG 2.0.0 by filtering with Med-PaLM 2 followed by verification by manual review by three US board-certified radiologists.

mimic-cxr labels

Published: Feb. 4, 2025. Version: 1.0.0

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Swiss-Mammo: A physician-written, synthetic dataset of German mammography reports

Daniel Reichenpfader, Sandro von Däniken, Harald Marcel Bonel

Swiss-Mammo: A physician-written, synthetic dataset of 28 German mammography reports. The dataset is stratified based on BI-RADS categories and available in German and English.

radiology mammography structured reporting bi-rads

Published: June 24, 2025. Version: 1.0.1

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MIMIC-Ext-CXR-QBA: A Structured, Tagged, and Localized Visual Question Answering Dataset with Question-Box-Answer Triplets and Scene Graphs for Chest X-ray Images

Philip Müller, Friederike Jungmann, Georgios Kaissis, et al.

We present a large-scale CXR VQA dataset derived from MIMIC-CXR with 42M QA pairs, featuring hierarchical answers, bounding boxes, and structured tags. We generated QA-pairs using LLM-based extraction from radiology reports and localization models.

chest x-rays vqa localization scene graphs

Published: July 22, 2025. Version: 1.0.0

Database Credentialed Access

LLaVA-Rad MIMIC-CXR Annotations

Juan Manuel Zambrano Chaves, Shih-Cheng Huang, Yanbo Xu, et al.

This dataset provides GPT-4 extracted sections of radiology reports from MIMIC-CXR, complementing rule-based section extractions with additional reports with findings, and removing references to priors from findings.

Published: Jan. 24, 2025. Version: 1.0.0