Resources

10 results for "chest x-ray interpretation"

Database Credentialed Access

Lunguage: A Benchmark for Structured and Sequential Chest X-ray Interpretation

Jong Hak Moon, Geon Choi, Paloma Rabaey, et al.

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 …
Published: Jan. 11, 2026. 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

Computer-aided diagnosis systems in adult chest radiography (CXR) have recently achieved great success thanks to the availability of large-scale, annotated datasets and the advent of high-performance supervised learning algorithms. However, the deve…
Published: March 21, 2022. Version: 1.0.0
Database Credentialed Access

Chest X-ray segmentation images based on MIMIC-CXR

Li-Ching Chen, Po-Chih Kuo, Ryan Wang, et al.

As more and more artificial intelligence (AI) or deep learning technologies have been applied to medical image applications such as radiological finding identification in chest X-rays (CXRs), the interpretability of the prediction model is crucial f…
Published: Aug. 18, 2022. Version: 1.0.0
Database Open Access

ReXErr-v1: Clinically Meaningful Chest X-Ray Report Errors Derived from MIMIC-CXR

Vishwanatha Rao, Serena Zhang, Julian Acosta, et al.

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…
Published: March 19, 2025. Version: 1.0.0
Database Credentialed Access

Eye Gaze Data for Chest X-rays

Alexandros Karargyris, Satyananda Kashyap, Ismini Lourentzou, et al.

We created a rich multimodal dataset for the Chest X-Ray (CXR) domain. The data was 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…
Published: Sept. 12, 2020. 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, et al.

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…
Published: June 22, 2021. Version: 1.0.0
Database Credentialed Access

Chest ImaGenome Dataset

Joy Wu, Nkechinyere Agu, Ismini Lourentzou, et al.

In recent years, with the release of multiple large datasets, automatic interpretation of chest X-ray (CXR) images with deep learning models have become feasible for specific abnormalities or for generating preliminary reports. However, despite repo…
Published: July 13, 2021. Version: 1.0.0
Database Credentialed Access

CXR-Align: A Benchmark for CXR-Report Alignment with Negations

Hanbin Ko

CXR-Align is a benchmark dataset designed to evaluate vision-language processing (VLP) models' ability to accurately interpret negations in chest X-ray (CXR) reports. Negations are prevalent in medical documentation and pose significant challenges f…
Published: Aug. 21, 2025. Version: 1.0.0
Database Credentialed Access

MIMIC-CXR-Ext-MIMIC-CXR-DB: Linking MIMIC-IV Chest Radiographs with Rich and Harmonized Clinical Context

Houcemeddine Turki, Lukman Ismaila, Ahmed Ben Salem, et al.

MIMIC-CXR-DB is a relational clinical database comprising 146,333 chest radiographs linked to hospital admissions, designed to support research at the intersection of electronic health records (EHRs) and chest radiography. The database integrates ho…
Published: Oct. 1, 2026. Version: 1.0
Database Credentialed Access

MIMIC-CXR-Ext-ReRef: A Radiologist-Validated Dataset of MIMIC-CXR Report Pairs Following Different Reporting Practices

Daniel Jeong, Charles Li, Hossein Hosseiny, et al.

Radiologists follow heterogeneous reporting practices: two radiologists examining the same image and identifying the same clinical findings might nevertheless compose superficially distinct reports, varying in terminology, shorthand, formatting, and…
Published: Oct. 30, 2026. Version: 1.0.0