Resources


Database Restricted Access

VinDr-PCXR: An open, large-scale pediatric chest X-ray dataset for interpretation of common thoracic diseases

Hieu Huy Pham, Tien Thanh Tran, Ha Quy Nguyen

An open, large-scale pediatric chest X-ray dataset that contains both lesion-level labels and image-level labels for multiple findings and diseases for interpretation of common thoracic diseases.

Published: March 21, 2022. Version: 1.0.0

Database Restricted Access

VinDr-SpineXR: A large annotated medical image dataset for spinal lesions detection and classification from radiographs

Hieu Huy Pham, Hieu Nguyen Trung, Ha Quy Nguyen

VinDr-SpineXR: A large annotated medical image dataset for spinal lesions detection and classification from radiographs

Published: Aug. 24, 2021. Version: 1.0.0

Database Restricted Access

CheXchoNet: A Chest Radiograph Dataset with Gold Standard Echocardiography Labels

Pierre Elias, Shreyas Bhave

Early detection of heart failure is vital for improving outcomes. The dataset contains 71,589 CXRs paired with gold standard labels from echocardiograms to enable the training of models to detect pathologies indicative of early stage heart failure.

heart failure chest x-rays deep learning early detection cardiac structural abnormalties

Published: March 20, 2024. Version: 1.0.0

Database Open Access

Heart and lung segmentations for MIMIC-CXR/MIMIC-CXR-JPG and Montgomery County TB databases

Benjamin Duvieusart, Felix Krones, Guy Parsons, Lionel Tarassenko, Bartlomiej W Papiez, Adam Mahdi

Heart and lung segmentations for 200 MIMIC-CXR/MIMIC-CXR-JPG chest x-rays and heart segmentations for 138 Montgomery County tuberculosis chest X-rays.

segmentation heart and lungs montgomery country tb mimic-cxr

Published: Aug. 14, 2023. Version: 1.0.0

Database Restricted Access

CheXchoNet: A Chest Radiograph Dataset with Gold Standard Echocardiography Labels

Pierre Elias, Shreyas Bhave

Early detection of heart failure is vital for improving outcomes. The dataset contains 71,589 CXRs paired with gold standard labels from echocardiograms to enable the training of models to detect pathologies indicative of early stage heart failure.

heart failure chest x-rays deep learning early detection cardiac structural abnormalties

Published: March 20, 2024. Version: 1.0.0

Database Credentialed Access

MIMIC-CXR-JPG - chest radiographs with structured labels

Alistair Johnson, Matthew 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 chest x-ray radiology deep learning

Published: March 12, 2024. Version: 2.1.0

Database Credentialed Access

CAD-Chest: Comprehensive Annotation of Diseases based on MIMIC-CXR Radiology Report

Mengliang Zhang, Xinyue Hu, Lin Gu, Tatsuya Harada, Kazuma Kobayashi, Ronald Summers, Yingying Zhu

The CAD-Chest dataset provides comprehensive annotations of disease, including disease severity, uncertainty, and location based on the MIMIC-CXR radiologist reports.

chesr x-ray disease label

Published: Dec. 8, 2023. Version: 1.0

Database Credentialed Access

MS-CXR-T: Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Shruthi Bannur, Stephanie Hyland, Qianchu Liu, Fernando Pérez-García, Max Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anton Schwaighofer, Maria Teodora Wetscherek, Hannah Richardson, Tristan Naumann, Javier Alvarez Valle, Ozan Oktay

The MS-CXR-T is a multimodal benchmark that enhances the MIMIC-CXR v2 dataset by including expert-verified annotations. Its goal is to evaluate biomedical visual-language processing models in terms of temporal semantics extracted from image and text.

multimodal chest x-ray radiology cxr disease progression vision-language processing

Published: March 17, 2023. 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, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez Valle, Hoifung Poon, Ozan Oktay

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.

chest x-ray vision-language processing

Published: May 16, 2022. Version: 0.1

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

Published: July 13, 2021. Version: 1.0.0