Dr. Yan Chen Profile

Dr. Yan Chen

at Univ of Nottingham

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Publications (3)

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Proceedings Article | 3 April 2023 Presentation + Paper

Challenges and solutions to processing and visualising eye tracking data from digital pathology studies

George J. W. Partridge, Peter Phillips, Adnan Taib, Yan Chen

Proceedings Volume 12467, 1246706 (2023) https://doi.org/10.1117/12.2652981

KEYWORDS: Eye tracking, Pathology, Displays, Eye, Visualization, Software development

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Digital Pathology (DP) reporting workstations permit eye tracking experiments which can aid our understanding of reading strategies and medical errors in pathology. However, eye tracking with DP slides is complex due to the nature of the slide viewing process: slide panning and zooming. Eye tracking technology records gaze coordinates to a screen surface, but these coordinates do not account for the ever-changing on-screen content (due to slide navigation), and therefore it is essential to track pathologists’ slide navigation to determine where on the slide the pathologist has viewed and what features were fixated. Additionally, visualising the resulting eye tracking data proves challenging due to the zooming component. Other eye tracking studies in DP have accounted for slide navigation by employing custom slide viewers that output slide movements as a data stream with the eye tracking data which are co-registered for analysis. We are conducting a DP eye tracking study using a commercial slide viewer which has been adopted at selected UK hospital sites, but slide movement data cannot be outputted as a data stream in this context. Therefore, we’re developing a software platform using computer vision techniques that can be applied to the recorded screen capture of the DP workstation which is synchronised with the eye tracking data. The developed algorithm could be adapted for use with other commercial slide viewers for future studies. Here, we explore how studies have addressed these issues and we discuss our approach.

Proceedings Article | 3 April 2023 Presentation + Paper

Identifying and preventing fatigue in digital breast tomosynthesis

Adnan Taib, George Partridge, Iain Darker, Peter Phillips, Yan Chen

Proceedings Volume 12467, 1246707 (2023) https://doi.org/10.1117/12.2654936

KEYWORDS: Digital breast tomosynthesis, Eye tracking, Diagnostics, Breast, Material fatigue, Displays, Cameras, Tunable filters, Statistical analysis, Signal detection

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Digital Breast Tomosynthesis (DBT) increases breast cancer detection rates but produces a significantly greater number of images for screeners to read compared to traditional two-dimensional (2-D) mammograms. Putting screeners at risk of fatigue and therefore error in detecting cancers.
The aim of this study was to explore if screeners showed differences in subjective fatigue, blink metrics and diagnostic accuracy during a DBT reading session with and without breaks.
Prospective study including 45 participants from 6 different hospital sites around England between December 2020 to April 2022. Non-intrusive, screen mounted eye tracking cameras (60Hz sampling rate) were set up in the participant’s natural reading environment. Forty DBT cases were read in a random order (47.5% malignant, 12.5% benign, 40% normal). Each breast was rated as normal or benign (return to screen) or indeterminate, suspicious or highly suspicious (recall). Twenty-one participants had a break at approximately 40 minutes into the session.
Participants without a break showed a significantly greater difference in subjective fatigue before and after the reporting session (44% vs 33%, p=0.037). Furthermore, those without breaks exhibited significantly greater blinks per minute (15.75 vs 13.25, p<0.001) and blink duration (milliseconds) (296 vs 286, p<0.001). There was no significant difference in overall accuracy between the cohorts (p=0.921).
Blink metrics have the potential to be used in identifying early onset of fatigue during reading sessions.

Proceedings Article | 4 April 2022 Presentation + Paper

Investigating reading strategies and eye behaviours associated with high diagnostic performance when reading digital breast tomosynthesis (DBT) images

George Partridge, Peter Phillips, Iain Darker, Yan Chen

Proceedings Volume 12035, 1203508 (2022) https://doi.org/10.1117/12.2611388

KEYWORDS: Eye, Digital breast tomosynthesis, Breast, Medical imaging, Cancer, Mammography, Cognition

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Purpose Digital breast tomosynthesis (DBT) exhibits increased sensitivity and specificity compared to 2D mammography (DM), but DBT images are complex and interpretation takes longer. Clinicians may fatigue or hit a cognitive limit sooner when reading DBT, potentially reducing diagnostic accuracy. Eye blink behaviour was investigated to explore fatigue and cognitive load. Methods Screeners (N=47) from five UK breast screening centres were eye tracked as they read 40 DBT cases (15 normal, 6 benign and 19 malignant), from November 2019-July 2021. Differences in diagnostic accuracy and blink behaviour were analysed over the course of the reading session. Blink rates and case durations were investigated by case malignancy and outcome using T-tests and ANOVAs (α=0.05). Results Blink rates were higher on malignant cases than on normal cases (p=0.004), and blink rates were higher for cases with true positive outcomes than for cases with true negative outcomes (p=0.013). Participants spent less time on malignant cases than normal or benign cases (ps=<0.0001), whilst spending more time on cases with a false positive outcome than on cases with a true negative or true positive outcome (ps<0.0001). No significant difference in blink rate or diagnostic performance by time through reporting session. Conclusion Differences in blink rate and time on case are associated with case malignancy and outcome, potentially reflecting varying cognitive demand and interpretation strategies. Further investigation into blinking during medical image interpretation may identify robust signals of cognition and fatigue that could be used for education and training purposes, whilst indicating optimal screening session duration.

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