Resources


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 structured radiology report named entity recognition

Published: Feb. 3, 2025. Version: 1.0.0

Database Restricted Access

MIMIC-Eye: Integrating MIMIC Datasets with REFLACX and Eye Gaze for Multimodal Deep Learning Applications

Chihcheng Hsieh, Chun Ouyang, Jacinto C Nascimento, et al.

MIMIC-Eye: Integrating MIMIC Datasets with REFLACX and Eye Gaze for Multimodal Deep Learning Applications

Published: March 23, 2023. Version: 1.0.0

Database Restricted Access

Smartphone-Captured Chest X-Ray Photographs

Po-Chih Kuo, ChengChe Tsai, Diego M Lopez, et al.

Smartphone-captured CXR images including photographs taken from MIMIC-CXR and CheXpert, photographs taken by resident doctors, and photographs taken with different devices.

smartphone photograph cxr

Published: Sept. 27, 2020. Version: 1.0.0

Database Credentialed Access

RadCoref: Fine-tuning coreference resolution for different styles of clinical narratives

Yuxiang Liao, Hantao Liu, Irena Spasic

RadCoref is a small subset of MIMIC-CXR with manually annotated coreference mentions and clusters. Based on the annotated data, we fine-tuned a deep neural model and used it to annotate the whole MIMIC-CXR dataset. Both data are available.

coreference resolution natural language processing radiology

Published: Jan. 30, 2024. Version: 1.0.0

Software Credentialed Access

Code for generating the HAIM multimodal dataset of MIMIC-IV clinical data and x-rays

Luis R Soenksen, Yu Ma, Cynthia Zeng, et al.

Code for generating the HAIM multimodal dataset of MIMIC-IV clinical data and x-rays

database code multimodality

Published: Aug. 23, 2022. Version: 1.0.1

Database Credentialed Access

Medical-CXR-VQA dataset: A Large-Scale LLM-Enhanced Medical Dataset for Visual Question Answering on Chest X-Ray Images

Xinyue Hu, Lin Gu, Kazuma Kobayashi, et al.

Medical-CXR-VQA provides a large-scale LLM-enhanced dataset for visual question answering in medical chest x-ray images.

Published: Jan. 21, 2025. Version: 1.0.0

Database Open Access

CheXmask-U: Uncertainty Estimation for Landmark-Based Anatomical Segmentation Masks in Chest X-ray Images

Matias Cosarinsky, Nicolas Gaggion, Enzo Ferrante

CheXmask-U provides anatomical segmentation masks of chest X-rays derived from landmarks with node-wise uncertainty estimates, enabling landmark-level and image-level analysis for uncertainty-aware research and robustness evaluation.

uncertainty-aware landmark segmentation

Published: Sept. 2, 2026. Version: 1.0.0

Database Open Access

CheXmask Database: a large-scale dataset of anatomical segmentation masks for chest x-ray images

Nicolas Gaggion, Candelaria Mosquera, Martina Aineseder, et al.

CheXmask Database is a 657,566 uniformly annotated chest radiographs with segmentation masks. Images were segmented using HybridGNet, with automatic quality control indicated by RCA scores.

automatic quality assesment chest x-ray segmentation medical image segmentation

Published: Jan. 22, 2025. Version: 1.0.0

Database Credentialed Access

EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images

Seongsu Bae, Daeun Kyung, Jaehee Ryu, et al.

We present EHRXQA, the first multi-modal EHR QA dataset combining structured patient records with aligned chest X-ray images. EHRXQA contains a comprehensive set of QA pairs covering image-related, table-related, and image+table-related questions.

question answering evaluation chest x-ray multi-modal question answering ehr question answering semantic parsing benchmark visual question answering electronic health records machine learning deep learning

Published: July 23, 2024. Version: 1.0.0

Database Credentialed Access

MS-CXR: Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, et al.

MS-CXR is a new dataset containing 1162 chest X-ray bounding box labels paired with radiology text descriptions, annotated and verified by two board-certified radiologists.

vision-language processing chest x-ray phrase grounding localization

Published: Nov. 15, 2024. Version: 1.1.0