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Proceedings Paper

Understanding digital pathology performance: an eye tracking study
Author(s): Amanda Koh; Dorina Roy; Alastair Gale; Raluca Mihai; Guprit Atwal; Ian Ellis; David Snead; Yan Chen
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Paper 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.

Paper Details

Date Published: 16 March 2020
PDF: 7 pages
Proc. SPIE 11316, Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment, 1131607 (16 March 2020); doi: 10.1117/12.2550513
Show Author Affiliations
Amanda Koh, The Univ. of Nottingham (United Kingdom)
Dorina Roy, The Univ. of Nottingham (United Kingdom)
Alastair Gale, Loughborough Univ. (United Kingdom)
Raluca Mihai, Nottingham Univ. Hospitals NHS Trust (United Kingdom)
Guprit Atwal, Nottingham Univ. Hospitals NHS Trust (United Kingdom)
Ian Ellis, Nottingham Univ. Hospitals NHS Trust (United Kingdom)
David Snead, Univ. Hospitals Coventry and Warwickshire NHS Trust (United Kingdom)
Yan Chen, The Univ. of Nottingham (United Kingdom)

Published in SPIE Proceedings Vol. 11316:
Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment
Frank W. Samuelson; Sian Taylor-Phillips, Editor(s)

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