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

Author Affiliations +

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

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Pathology

Eye

Diagnostics

Breast

Digital imaging

Microscopy

Visualization

Show All Keywords

Keywords/Phrases

Search In:

Publication Years