Understanding digital pathology performance: an eye tracking study

Amanda Koh; Dorina Roy; Alastair Gale; Raluca Mihai; Guprit Atwal; Ian Ellis; David Snead; Yan Chen

doi:10.1117/12.2550513

16 March 2020 Understanding digital pathology performance: an eye tracking study

Amanda Koh, Dorina Roy, Alastair Gale, Raluca Mihai, Guprit Atwal, Ian Ellis, David Snead, Yan Chen

Proceedings Volume 11316, Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment; 1131607 (2020) https://doi.org/10.1117/12.2550513
Event: SPIE Medical Imaging, 2020, Houston, Texas, United States

Abstract

Pathology in the UK is on the verge of transformation from analogue to digital practice through the development of digital pathology (DP). Advances in technology has allowed for this change to occur through the use of high-throughput slide scanners to obtain whole histopathology glass slides onto computer workstations rather than the use of a conventional light microscope (LM). Previous studies have shown that the use of digital imaging to view histopathology slides has proven to be of benefit to pathology departments. It allows pathologists to analyse samples remote from the laboratory, making sharing of the slides between pathologists more straight-forward, and also enables expert review out of hours. With the ability to electronically transfer slides from the laboratory to the reporting pathologist, it may provide solutions for local shortages of pathologists across NHS trusts in the UK. However, a number of researchers argue that the costs of implementing digital pathology may outweigh its advantages. Moreover, images produced by DP systems are often of inferior resolution when compared to conventional light microscopy. The lack of literature on this subject limits the adoption of this new technology by laboratories across the country. This multi-centre study aims to analyse how the study pathologists examine DP images of different pathology modalities by using eye-tracking technology, thus using data on their reading and interpretation technique to improve performance and contribute to the adoption of DP across the UK.

Citation Download Citation

Amanda Koh, Dorina Roy, Alastair Gale, Raluca Mihai, Guprit Atwal, Ian Ellis, David Snead, and Yan Chen "Understanding digital pathology performance: an eye tracking study", Proc. SPIE 11316, Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment, 1131607 (16 March 2020); https://doi.org/10.1117/12.2550513

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KEYWORDS

Pathology

Eye

Diagnostics

Breast

Digital imaging

Microscopy

Visualization

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