Spatial and time domain analysis of eye-tracking data during screening of brain magnetic resonance images

Journal article


Suman, Abdulla Al, Russo, Carlo, Carrigan, Ann, Nalepka, Patrick, Liquet-Weiland, Benoit, Newport, Robert Ahadizad, Kumari, Poonam and Ieva, Antonio Di. (2021). Spatial and time domain analysis of eye-tracking data during screening of brain magnetic resonance images. PLoS One. 16, pp. 1-19. https://doi.org/10.1371/journal.pone.0260717
AuthorsSuman, Abdulla Al, Russo, Carlo, Carrigan, Ann, Nalepka, Patrick, Liquet-Weiland, Benoit, Newport, Robert Ahadizad, Kumari, Poonam and Ieva, Antonio Di
Abstract

Introduction: Eye-tracking research has been widely used in radiology applications. Prior studies exclusively analysed either temporal or spatial eye-tracking features, both of which alone do not completely characterise the spatiotemporal dynamics of radiologists’ gaze features.

Purpose: Our research aims to quantify human visual search dynamics in both domains during brain stimuli screening to explore the relationship between reader characteristics and stimuli complexity. The methodology can be used to discover strategies to aid trainee radiologists in identifying pathology, and to select regions of interest for machine vision applications.

Method: The study was performed using eye-tracking data 5 seconds in duration from 57 readers (15 Brain-experts, 11 Other-experts, 5 Registrars and 26 Naïves) for 40 neuroradiological images as stimuli (i.e., 20 normal and 20 pathological brain MRIs). The visual scanning patterns were analysed by calculating the fractal dimension (FD) and Hurst exponent (HE) using re-scaled range (R/S) and detrended fluctuation analysis (DFA) methods. The FD was used to measure the spatial geometrical complexity of the gaze patterns, and the HE analysis was used to measure participants’ focusing skill. The focusing skill is referred to persistence/anti-persistence of the participants’ gaze on the stimulus over time. Pathological and normal stimuli were analysed separately both at the “First Second” and full “Five Seconds” viewing duration.

Results: All experts were more focused and a had higher visual search complexity compared to Registrars and Naïves. This was seen in both the pathological and normal stimuli in the first and five second analyses. The Brain-experts subgroup was shown to achieve better focusing skill than Other-experts due to their domain specific expertise. Indeed, the FDs found when viewing pathological stimuli were higher than those in normal ones. Viewing normal stimuli resulted in an increase of FD found in five second data, unlike pathological stimuli, which did not change. In contrast to the FDs, the scanpath HEs of pathological and normal stimuli were similar. However, participants’ gaze was more focused for “Five Seconds” than “First Second” data.

Conclusions: The HE analysis of the scanpaths belonging to all experts showed that they have greater focus than Registrars and Naïves. This may be related to their higher visual search complexity than non-experts due to their training and expertise.

Keywordsradiology; radiologists; vision; imaging; fractals; eye movements; time series analysis; dwell time
Year01 Jan 2021
JournalPLoS One
Journal citation16, pp. 1-19
PublisherPublic Library of Science (PLoS)
ISSN1932-6203
Digital Object Identifier (DOI)https://doi.org/10.1371/journal.pone.0260717
Web address (URL)https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0260717
Open accessOpen access
Research or scholarlyResearch
Page range1-19
Publisher's version
License
File Access Level
Open
Output statusPublished
Publication dates
Online02 Dec 2021
Publication process dates
Accepted15 Nov 2021
Deposited20 Sep 2024
Additional information

© 2021 Suman et al.

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

All relevant data files and code are available from the following Github public repository link https://github.com/Abdulla-Al-Suman/Eye-Tracking-on-Brain-MRI.

Place of publicationUnited States
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