Resources

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.

Chest radiographs in DICOM format with associated free-text reports.

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.

CXR-PRO is an adaptation of the MIMIC-CXR dataset (consisting of chest radiographs and their associated free-text radiology reports) with references to non-existent priors removed.

Chest x-rays in JPG format with structured labels derived from the associated radiology report.

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.

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

RadGraph is a dataset of entities and relations in full-text chest X-ray radiology reports, which are obtained using a novel information extraction (IE) schema to capture clinically relevant information in a radiology report.

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

Smartphone-captured CXR images including photographs taken from MIMIC-CXR and CheXpert, photographs taken by resident doctors, and photographs taken with different devices.