Resources
37 results for "chest x-ray imaging"
Database
Open Access
CheXmask-U: Uncertainty Estimation for Landmark-Based Anatomical Segmentation Masks in Chest X-ray Images
We present an extended version of the CheXmask dataset, augmenting the original anatomical segmentation masks of chest X-rays with node-wise uncertainty estimates. The dataset retains the comprehensive coverage of five public sources—ChestX-ray8, Ch…
Database
Credentialed Access
MIMIC-Ext-CXR-QBA: A Structured, Tagged, and Localized Visual Question Answering Dataset with Question-Box-Answer Triplets and Scene Graphs for Chest X-ray Images
Visual Question Answering (VQA) enables flexible and context-dependent analysis of medical images, such as chest X-rays (CXRs), by allowing users to pose specific questions and receive nuanced answers. However, existing CXR VQA datasets are typicall…
Database
Restricted Access
LATTE-CXR: Locally Aligned TexT and imagE, Explainable dataset for Chest X-Rays
Local annotation of medical data is both expensive and time-consuming due to the high cost of expert annotators, the precision required for accurate annotation, and the inherent challenges of medical diagnosis. To address these problems, we develop…
Database
Credentialed Access
Medical-Diff-VQA: A Large-Scale Medical Dataset for Difference Visual Question Answering on Chest X-Ray Images
The task of Difference Visual Question Answering involves answering questions about the difference between a pair of main and reference images. This process is consistent with the radiologist's diagnosis practice that compares the current image with…
Database
Open Access
CheXmask Database: a large-scale dataset of anatomical segmentation masks for chest x-ray images
The CheXmask Database presents a comprehensive, uniformly annotated collection of chest radiographs, constructed from five public databases: ChestX-ray8, Chexpert, MIMIC-CXR-JPG, Padchest and VinDr-CXR. The database aggregates 657,566 anatomical seg…
Database
Credentialed Access
Medical-CXR-VQA dataset: A Large-Scale LLM-Enhanced Medical Dataset for Visual Question Answering on Chest X-Ray Images
Medical Visual Question Answering (VQA) is an important task in medical multi-modal Large Language Models (LLMs), aiming to answer clinically relevant questions regarding input medical images. This technique has the potential to improve the efficien…
Database
Open Access
Image-derived cardiomegaly biomarker values for 96K chest X-rays in MIMIC-CXR/MIMIC-CXR-JPG
Cardiomegaly is a condition characterized by an abnormal enlargement of the heart, its identification is of paramount importance as it associate with a wide range of cardiac conditions. It is primary identified via the cardiothoracic ratio (CTR), ho…
Database
Credentialed Access
EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images
Electronic Health Records (EHRs), which contain patients' medical histories in various multi-modal formats, often overlook the potential for joint reasoning across imaging and table modalities underexplored in current EHR Question Answering (QA) sys…
Database
Credentialed Access
MIMIC-Ext-MIMIC-CXR-VQA: A Complex, Diverse, And Large-Scale Visual Question Answering Dataset for Chest X-ray Images
We introduce MIMIC-Ext-MIMIC-CXR-VQA (i.e., Extended from MIMIC database), a complex, diverse, and large-scale dataset designed for Visual Question Answering (VQA) tasks within the medical domain, focusing primarily on chest radiographs. This datase…
Database
Credentialed Access
Generalized Image Embeddings for the MIMIC Chest X-Ray dataset
This database contains image embeddings from the DICOM images of the MIMIC V2.0.0 Chest X-Ray database, generated using the approach described in “Simplified Transfer Learning for Chest Radiography Models Using Less Data”. The image embeddings are c…