Resources


Database Open Access

Radiology Report Generation Models Evaluation Dataset For Chest X-rays (RadEvalX)

Amos Rubin Calamida, Farhad Nooralahzadeh, Morteza Rohanian, et al.

The RadEvalX is a publicly available dataset developed similarly to the ReXVal dataset. RedEvalX focuses on radiologist evaluations of errors found in automatically generated radiology reports.

Published: June 18, 2024. Version: 1.0.0

Database Restricted Access

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

Database Credentialed Access

Radiology Report Expert Evaluation (ReXVal) Dataset

Feiyang Yu, Mark Endo, Rayan Krishnan, et al.

The Radiology Report Expert Evaluation (ReXVal) Dataset is a publicly available dataset of radiologist evaluations of errors in automatically generated radiology reports.

Published: June 20, 2023. Version: 1.0.0

Database Credentialed Access

RaDialog Instruct Dataset

Chantal Pellegrini, Ege Özsoy, Benjamin Busam, et al.

Image-based instruct data for Chest X-Ray understanding and analysis.

medical image understaning radiology chatbot radiology report generation radiology assistant large vision-language models

Published: July 12, 2024. Version: 1.1.0

Database Credentialed Access

RaDialog Instruct Dataset

Chantal Pellegrini, Ege Özsoy, Benjamin Busam, et al.

Image-based instruct data for Chest X-Ray understanding and analysis.

medical image understaning radiology chatbot radiology report generation radiology assistant large vision-language models

Published: July 12, 2024. Version: 1.1.0

Database Credentialed Access

RaDialog Instruct Dataset

Chantal Pellegrini, Ege Özsoy, Benjamin Busam, et al.

Image-based instruct data for Chest X-Ray understanding and analysis.

medical image understaning radiology chatbot radiology report generation radiology assistant large vision-language models

Published: July 12, 2024. Version: 1.1.0

Model Credentialed Access

RadVLM model

Nicolas Deperrois, Hidetoshi Matsuo, Samuel Ruiperez-Campillo, et al.

RadVLM is a 7B-parameter vision-language model fine-tuned on public chest-X-ray data that drafts reports, lists abnormalities, grounds findings, and chats about a CXR through a single image-to-text interface.

Published: Oct. 8, 2025. Version: 1.0.0

Database Credentialed Access

RadVLM Instruction Dataset

Nicolas Deperrois, Hidetoshi Matsuo, Samuel Ruiperez-Campillo, et al.

This dataset is designed to construct RadVLM, a vision–language model for chest X-ray interpretation. It includes instruction data for tasks such as report generation, abnormality detection, and region grounding, and multitask conversation.

chest x-rays vision-language models medical ai

Published: Sept. 25, 2025. Version: 1.0.0

Database Restricted Access

LATTE-CXR: Locally Aligned TexT and imagE, Explainable dataset for Chest X-Rays

Elham Ghelichkhan, Tolga Tasdizen

This dataset includes bounding box-statement pairs for chest X-ray images, derived from radiologists’ eye-tracking data (for explainability) and annotations, for local visual-language models.

eye-tracking chest x-ray dataset automatically generated dataset caption-guided object detection image captioning with region-level description grounded radiology report generation phrase grounding xai multi-modal learning local visual-language models localization

Published: Feb. 4, 2025. Version: 1.0.0

Database Restricted Access

LATTE-CXR: Locally Aligned TexT and imagE, Explainable dataset for Chest X-Rays

Elham Ghelichkhan, Tolga Tasdizen

This dataset includes bounding box-statement pairs for chest X-ray images, derived from radiologists’ eye-tracking data (for explainability) and annotations, for local visual-language models.

eye-tracking chest x-ray dataset automatically generated dataset caption-guided object detection image captioning with region-level description grounded radiology report generation phrase grounding xai multi-modal learning local visual-language models localization

Published: Feb. 4, 2025. Version: 1.0.0