Resources


Database Credentialed Access

Chest X-ray Dataset with Lung Segmentation

Wimukthi Indeewara, Mahela Hennayake, Kasun Rathnayake, et al.

CXLSeg dataset: Chest X-ray with Lung Segmentation, a comparatively large dataset of segmented Chest X-ray radiographs based on the MIMIC-CXR dataset. This contains segmentation results of 243,324 frontal view images and corresponding masks.

segmentation medical reports u-net chest radiographs mimic-cxr chest x-ray

Published: Feb. 8, 2023. Version: 1.0.0

Database Restricted Access

REFLACX: Reports and eye-tracking data for localization of abnormalities in chest x-rays

Ricardo Bigolin Lanfredi, Mingyuan Zhang, William Auffermann, et al.

This dataset contains 3032 cases of eye-tracking data collected while five radiologists dictated reports for frontal chest x-rays, synchronized timestamped dictation transcription, and manual labels for validation of localization of abnormalities.

eye tracking radiology report reflacx fixations chest x-rays computer vision gaze machine learning radiology deep learning

Published: Sept. 27, 2021. Version: 1.0.0

Database Credentialed Access

BRAX, a Brazilian labeled chest X-ray dataset

Eduardo Pontes Reis, Joselisa Paiva, Maria Carolina Bueno da Silva, et al.

BRAX contains 24,959 chest radiography exams and 40,967 images acquired in a large general Brazilian hospital. All images have been read by trained radiologists and 14 labels were derived from Brazilian Portuguese reports using NLP.

chest x-ray dataset artificial intelligence

Published: June 17, 2022. Version: 1.1.0

Database Open Access

Radiology Report Generation Models Evaluation Dataset For Chest X-rays (RadEvalX)

Amos Rubin Calamida, Farhad Nooralahzadeh, Morteza Rohanian, et al.

The RadEvalX is a publicly available dataset developed similarly to the ReXVal dataset. RedEvalX focuses on radiologist evaluations of errors found in automatically generated radiology reports.

Published: June 18, 2024. Version: 1.0.0

Software Credentialed Access

Code for generating the HAIM multimodal dataset of MIMIC-IV clinical data and x-rays

Luis R Soenksen, Yu Ma, Cynthia Zeng, et al.

Code for generating the HAIM multimodal dataset of MIMIC-IV clinical data and x-rays

database code multimodality

Published: Aug. 23, 2022. Version: 1.0.1

Database Credentialed Access

CXReasonBench: A Benchmark for Evaluating Structured Diagnostic Reasoning in Chest X-rays

Hyungyung Lee, Geon Choi, Jung Oh Lee, et al.

CheXStruct is an automated pipeline that derives structured diagnostic reasoning steps from chest X-rays. CXReasonBench builds on this to evaluate whether models perform clinically grounded, multi-step reasoning beyond final diagnoses.

evaluation chest x-ray benchmark structured chest x-ray qa intermediate reasoning steps structured reasoning grounded reasoning diagnostic reasoning structured diagnostic pipeline

Published: Oct. 23, 2025. Version: 1.0.1

Database Restricted Access

LATTE-CXR: Locally Aligned TexT and imagE, Explainable dataset for Chest X-Rays

Elham Ghelichkhan, Tolga Tasdizen

This dataset includes bounding box-statement pairs for chest X-ray images, derived from radiologists’ eye-tracking data (for explainability) and annotations, for local visual-language models.

eye-tracking chest x-ray dataset automatically generated dataset caption-guided object detection image captioning with region-level description grounded radiology report generation phrase grounding xai multi-modal learning local visual-language models localization

Published: Feb. 4, 2025. Version: 1.0.0

Database Credentialed Access

MIMIC-CXR-Ext-ILS: Lesion Segmentation Masks and Instruction-Answer Pairs for Chest X-rays

Geon Choi, Hangyul Yoon, Hyunju Shin, et al.

Instruction-guided lesion segmentation data for chest X-rays, including 1.1M instruction-answer pairs and 91K segmentation masks covering seven major lesion types.

chest x-ray segmentation text-guided segmentation lesion segmentation

Published: March 25, 2026. Version: 1.0.0

Database Credentialed Access

Eye Gaze Data for Chest X-rays

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

This dataset was a 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, transcribed report text, dictation audio and eye gaze data.

convolutional network heatmap eye tracking explainability audio chest cxr machine learning chest x-ray radiology deep learning multimodal

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.

VinDr-CXR: An open dataset of chest X-rays with radiologist's annotations

lesion detection chest x-ray interpretation disease classification computer vision deep learning

Published: June 22, 2021. Version: 1.0.0