Eye Gaze Data for Chest X-rays

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, transcribed report text, dictation audio
and eye gaze data. We hope this dataset can contribute to various fields of
research with applications in machine learning such as deep learning
explainability, multi-modal fusion, disease classification, and automated
radiology report generation to name a few. The images were selected from the
MIMIC-CXR Database and were associated with studies from 1,038 subjects
(female: 495, male: 543) who had age range 20 - 80 years old.