AI-based analysis of radiologist's eye movements for fatigue estimation: A pilot study on chest X-rays
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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.
Originalsprog | Engelsk |
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Titel | Medical Imaging 2022 : Image Perception, Observer Performance, and Technology Assessment |
Redaktører | Claudia R. Mello-Thoms, Claudia R. Mello-Thoms, Sian Taylor-Phillips |
Antal sider | 4 |
Forlag | SPIE |
Publikationsdato | 2022 |
Artikelnummer | 120350Y |
ISBN (Elektronisk) | 9781510649453 |
DOI | |
Status | Udgivet - 2022 |
Begivenhed | Medical Imaging 2022: Image Perception, Observer Performance, and Technology Assessment - Virtual, Online Varighed: 21 mar. 2022 → 27 mar. 2022 |
Konference
Konference | Medical Imaging 2022: Image Perception, Observer Performance, and Technology Assessment |
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By | Virtual, Online |
Periode | 21/03/2022 → 27/03/2022 |
Sponsor | The Society of Photo-Optical Instrumentation Engineers (SPIE) |
Navn | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
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Vol/bind | 12035 |
ISSN | 1605-7422 |
Bibliografisk note
Funding Information:
This research was supported by the Russian Science Foundation under Grant no.18-71-10072.
Publisher Copyright:
© 2022 SPIE. All rights reserved.
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