Resources


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 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

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 Open Access

CheXmask Database: a large-scale dataset of anatomical segmentation masks for chest x-ray images

Nicolas Gaggion, Candelaria Mosquera, Martina Aineseder, et al.

CheXmask Database is a 657,566 uniformly annotated chest radiographs with segmentation masks. Images were segmented using HybridGNet, with automatic quality control indicated by RCA scores.

automatic quality assesment chest x-ray segmentation medical image segmentation

Published: Jan. 22, 2025. Version: 1.0.0

Database Credentialed Access

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

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

A radiologist-annotated benchmark of structured chest X-ray reports at single and sequential levels, comprising 1,473 reports across 18 relation types and 80 longitudinal cases.

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

Published: Jan. 11, 2026. Version: 1.0.0

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

Philip Müller, Friederike Jungmann, Georgios Kaissis, et al.

We present a large-scale CXR VQA dataset derived from MIMIC-CXR with 42M QA pairs, featuring hierarchical answers, bounding boxes, and structured tags. We generated QA-pairs using LLM-based extraction from radiology reports and localization models.

chest x-rays vqa localization scene graphs

Published: July 22, 2025. Version: 1.0.0

Database Credentialed Access

Symile-MIMIC: a multimodal clinical dataset of chest X-rays, electrocardiograms, and blood labs from MIMIC-IV

Adriel Saporta, Aahlad Manas Puli, Mark Goldstein, et al.

A multimodal clinical dataset consisting of CXRs, ECGs, and blood labs, designed to evaluate Symile, a simple contrastive loss that accommodates any number of modalities and allows any model to produce representations for each modality.

database cxr ecg chest x-ray electrocardiogram contrastive learning model multimodal mimic

Published: Jan. 28, 2025. Version: 1.0.0

Database Credentialed Access

EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images

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

We present EHRXQA, the first multi-modal EHR QA dataset combining structured patient records with aligned chest X-ray images. EHRXQA contains a comprehensive set of QA pairs covering image-related, table-related, and image+table-related questions.

question answering machine learning electronic health records evaluation chest x-ray multi-modal question answering ehr question answering semantic parsing deep learning benchmark visual question answering

Published: July 23, 2024. 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.

A chest x-rays segmentation dataset derived from MIMIC-CXR based on deep learning algorithm and human examination.

segmentation chest x-rays cxr

Published: Aug. 18, 2022. Version: 1.0.0