Resources


Database Credentialed Access

Chest ImaGenome Dataset

Joy Wu, Nkechinyere Agu, Ismini Lourentzou, Arjun Sharma, Joseph Paguio, Jasper Seth Yao, Edward Christopher Dee, William Mitchell, Satyananda Kashyap, Andrea Giovannini, Leo Anthony Celi, Tanveer Syeda-Mahmood, Mehdi Moradi

The Chest ImaGenome dataset is a scene graph dataset with additional chronological comparison relations for chest X-rays. It is automatically derived from the MIMIC-CXR dataset. A manually annotated gold standard is also available for 500 patients.

multimodal radiology chest x-ray machine learning scene graph visual question answering visual dialogue object detection disease progression semantic reasoning bounding box relation extraction knowledge graph explainability reasoning chest cxr deep learning

Published: July 13, 2021. Version: 1.0.0


Database Credentialed Access

Eye Gaze Data for Chest X-rays

Alexandros Karargyris, Satyananda Kashyap, Ismini Lourentzou, Joy Wu, Matthew Tong, Arjun Sharma, Shafiq Abedin, David Beymer, Vandana Mukherjee, Elizabeth Krupinski, Mehdi Moradi

This dataset was a collected using an eye tracking system while a radiologist interpreted and read 1,083 public CXR images. The dataset contains the following aligned modalities: image, transcribed report text, dictation audio and eye gaze data.

audio convolutional network heatmap multimodal radiology eye tracking chest x-ray machine learning explainability chest cxr deep learning

Published: Sept. 12, 2020. Version: 1.0.0


Database Credentialed Access

MIMIC-CXR Database

Alistair Johnson, Tom Pollard, Roger Mark, Seth Berkowitz, Steven Horng

Chest radiographs in DICOM format with associated free-text reports.

mimic computer vision radiology chest x-rays machine learning natural language processing

Published: Sept. 19, 2019. Version: 2.0.0


Database Restricted Access

REFLACX: Reports and eye-tracking data for localization of abnormalities in chest x-rays

Ricardo Bigolin Lanfredi, Mingyuan Zhang, William Auffermann, Jessica Chan, Phuong-Anh Duong, Vivek Srikumar, Trafton Drew, Joyce Schroeder, Tolga Tasdizen

This dataset contains 3032 cases of eye-tracking data collected while five radiologists dictated reports for frontal chest x-rays, synchronized timestamped dictation transcription, and manual labels for validation of localization of abnormalities.

computer vision radiology eye tracking radiology report chest x-rays machine learning reflacx fixations gaze deep learning

Published: Sept. 27, 2021. Version: 1.0.0


Database Credentialed Access

CXR-PRO: MIMIC-CXR with Prior References Omitted

Vignav Ramesh, Nathan Chi, Pranav Rajpurkar

CXR-PRO is an adaptation of the MIMIC-CXR dataset (consisting of chest radiographs and their associated free-text radiology reports) with references to non-existent priors removed.

generation large language models free-text radiology reports references to priors retrieval

Published: Nov. 23, 2022. Version: 1.0.0


Database Credentialed Access

VinDr-CXR: An open dataset of chest X-rays with radiologist annotations

Ha Quy Nguyen, Hieu Huy Pham, le tuan linh, Minh Dao, lam khanh

VinDr-CXR: An open dataset of chest X-rays with radiologist's annotations

computer vision lesion detection disease classification chest x-ray interpretation deep learning

Published: June 22, 2021. Version: 1.0.0


Database Credentialed Access

MIMIC-CXR-JPG - chest radiographs with structured labels

Alistair Johnson, Matt Lungren, Yifan Peng, Zhiyong Lu, Roger Mark, Seth Berkowitz, Steven Horng

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

mimic computer vision radiology chest x-ray deep learning

Published: Nov. 14, 2019. Version: 2.0.0


Database Credentialed Access

Chest X-ray segmentation images based on MIMIC-CXR

Li-Ching Chen, Po-Chih Kuo, Ryan Wang, Judy Gichoya, Leo Anthony Celi

A chest x-rays segmentation dataset derived from MIMIC-CXR based on deep learning algorithm and human examination.

segmentation chest x-rays cxr

Published: Aug. 18, 2022. Version: 1.0.0


Database Credentialed Access

RadGraph: Extracting Clinical Entities and Relations from Radiology Reports

Saahil Jain, Ashwin Agrawal, Adriel Saporta, Steven QH Truong, Du Nguyen Duong, Tan Bui, Pierre Chambon, Matthew Lungren, Andrew Ng, Curtis Langlotz, Pranav Rajpurkar

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.

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

Published: June 3, 2021. Version: 1.0.0


Database Restricted Access

Smartphone-Captured Chest X-Ray Photographs

Po-Chih Kuo, ChengChe Tsai, Diego M Lopez, Alexandros Karargyris, Tom Pollard, Alistair Johnson, Leo Anthony Celi

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