Resources


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 Credentialed Access

MIMIC-Ext-MIMIC-CXR-VQA: A Complex, Diverse, And Large-Scale Visual Question Answering Dataset for Chest X-ray Images

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

We introduce MIMIC-Ext-MIMIC-CXR-VQA, a complex, diverse, and large-scale dataset designed for Visual Question Answering (VQA) tasks within the medical domain, focusing primarily on chest radiographs.

question answering machine learning electronic health records evaluation chest x-ray radiology benchmark multimodal deep learning visual question answering

Published: July 19, 2024. Version: 1.0.0

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.

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

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, et al.

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.

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

Published: March 20, 2024. Version: 1.0.0

Database Restricted Access

Visual Question Answering evaluation dataset for MIMIC CXR

Timo Kohlberger, Charles Lau, Tom Pollard, et al.

This dataset provides 224 VQAs for 40 test set cases, and 111 VQAs for 23 validation set cases of the MIMIC CXR dataset.

Published: Jan. 28, 2025. Version: 1.0.0

Database Credentialed Access

ReXPref-Prior: A MIMIC-CXR Preference Dataset for Reducing Hallucinated Prior Exams in Radiology Report Generation

Oishi Banerjee, Hong-Yu Zhou, Subathra Adithan, et al.

We propose ReXPref-Prior, an adapted version of MIMIC-CXR where GPT-4 has removed references to prior exams from both findings and impression sections of chest X-ray reports.

chest x-rays reinforcement learning hallucination

Published: Aug. 14, 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