Resources
49 results for "chest x-ray"
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…
Database
Credentialed Access
VinDr-CXR: An open dataset of chest X-rays with radiologist annotations
We describe here a dataset of more than 100,000 chest X-ray scans that were retrospectively collected from two major hospitals in Vietnam. Out of this raw data, we release 18,000 images that were manually annotated by a total of 17 experienced radio…
Database
Restricted Access
Smartphone-Captured Chest X-Ray Photographs
Recent research has applied deep learning imaging techniques to detect pulmonary pathology in chest X-rays (CXR) and achieved performance comparable with radiologists on specific lung abnormalities. Industry has managed to deploy such artificial int…
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
Credentialed Access
Lunguage: A Benchmark for Structured and Sequential Chest X-ray Interpretation
Radiology reports convey detailed clinical observations and capture diagnostic reasoning that evolves over time. However, existing evaluation methods are limited to single-report settings and rely on coarse metrics that fail to capture fine-grained …
fine-grained structured reports
attribute-level clinical reasoning
medical text structuring
longitudinal clinical reasoning
chest x-ray report parsing
medical information structuring
benchmark dataset for radiology report
medical information extraction
structured radiology reports
temporal relation extraction
radiology report benchmarking
longitudinal clinical understanding
Database
Open Access
ReXErr-v1: Clinically Meaningful Chest X-Ray Report Errors Derived from MIMIC-CXR
Interpreting medical images and writing radiology reports is a critical yet challenging task in healthcare. Despite their importance, both human-written and AI-generated reports are liable to errors, leaving a need for robust and representative data…
Database
Credentialed Access
Symile-MIMIC: a multimodal clinical dataset of chest X-rays, electrocardiograms, and blood labs from MIMIC-IV
Symile-MIMIC is a multimodal clinical dataset derived from MIMIC-IV and MIMIC-CXR, consisting of chest X-rays (CXRs), electrocardiograms (ECGs), and blood laboratory tests. It was developed to evaluate Symile, a contrastive learning objective design…
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…