REFLACX, a dataset of reports and eye-tracking data for localization of abnormalities in chest x-rays

Deep learning has shown recent success in classifying anomalies in chest x-rays, but datasets are still small compared to natural image datasets. Supervision of abnormality localization has been shown to improve trained models, partially compensating for dataset sizes. However, explicitly labeling t...

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Bibliographic Details
Published in:Scientific data 2022-06, Vol.9 (1), p.350-350, Article 350
Main Authors: Bigolin Lanfredi, Ricardo, Zhang, Mingyuan, Auffermann, William F., Chan, Jessica, Duong, Phuong-Anh T., Srikumar, Vivek, Drew, Trafton, Schroeder, Joyce D., Tasdizen, Tolga
Format: Article
Language:English
Subjects:
639/705/117
692/700/1421/1770
Chest
Data Descriptor
Datasets
Deep Learning
Eye-Tracking Technology
Humanities and Social Sciences
Humans
Localization
multidisciplinary
Radiography
Radiography, Thoracic
Radiology
Science
Science (multidisciplinary)
X-Rays
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Summary:Deep learning has shown recent success in classifying anomalies in chest x-rays, but datasets are still small compared to natural image datasets. Supervision of abnormality localization has been shown to improve trained models, partially compensating for dataset sizes. However, explicitly labeling these anomalies requires an expert and is very time-consuming. We propose a potentially scalable method for collecting implicit localization data using an eye tracker to capture gaze locations and a microphone to capture a dictation of a report, imitating the setup of a reading room. The resulting REFLACX (Reports and Eye-Tracking Data for Localization of Abnormalities in Chest X-rays) dataset was labeled across five radiologists and contains 3,032 synchronized sets of eye-tracking data and timestamped report transcriptions for 2,616 chest x-rays from the MIMIC-CXR dataset. We also provide auxiliary annotations, including bounding boxes around lungs and heart and validation labels consisting of ellipses localizing abnormalities and image-level labels. Furthermore, a small subset of the data contains readings from all radiologists, allowing for the calculation of inter-rater scores. Measurement(s) gaze locations • radiology report • abnormality localizations • chest localization (lung and heart) • abnormality presence Technology Type(s) eye tracking device • Microphone Device • User Interface Device Sample Characteristic - Organism Homo sapiens
ISSN:2052-4463
2052-4463
DOI:10.1038/s41597-022-01441-z