AI-based analysis of radiologist’s eye movements for fatigue estimation: a pilot study on chest X-rays

Ilya Pershin; Maksim Kholiavchenko; Bulat Maksudov; Tamerlan Mustafaev; Bulat Ibragimov

doi:10.1117/12.2612760

4 April 2022 AI-based analysis of radiologist’s eye movements for fatigue estimation: a pilot study on chest X-rays

Ilya Pershin, Maksim Kholiavchenko, Bulat Maksudov, Tamerlan Mustafaev, Bulat Ibragimov

Proceedings Volume 12035, Medical Imaging 2022: Image Perception, Observer Performance, and Technology Assessment; 120350Y (2022) https://doi.org/10.1117/12.2612760
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Abstract

Radiologist-AI interaction is a novel area of research of potentially great impact. It has been observed in the literature that the radiologists’ performance deteriorates towards the shift ends and there is a visual change in their gaze patterns. However, the quantitative features in these patterns that would be predictive of fatigue have not yet been discovered. A radiologist was recruited to read chest X-rays, while his eye movements were recorded. His fatigue was measured using the target concentration test and Stroop test having the number of analyzed X-rays being the reference fatigue metric. A framework with two convolutional neural networks based on UNet and ResNeXt50 architectures was developed for the segmentation of lung fields. This segmentation was used to analyze radiologist’s gaze patterns. With a correlation coefficient of 0.82, the eye gaze features extracted lung segmentation exhibited the strongest fatigue predictive powers in contrast to alternative features.

Conference Presentation

Citation Download Citation

Ilya Pershin, Maksim Kholiavchenko, Bulat Maksudov, Tamerlan Mustafaev, and Bulat Ibragimov "AI-based analysis of radiologist’s eye movements for fatigue estimation: a pilot study on chest X-rays", Proc. SPIE 12035, Medical Imaging 2022: Image Perception, Observer Performance, and Technology Assessment, 120350Y (4 April 2022); https://doi.org/10.1117/12.2612760

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available