Development of a digital platform to aid chest radiographic image interpretation

Laura Mclaughlin, RR Bond, Ciara Hughes, Jonathan McConnell, Nick Woznitza, Ayman Elsayed, Andrew Cairns, Derwar Finlay, Sonyia McFadden

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Training has been provided in a variety of methods and tested for its effect on image interpretation accuracy. Studies have attempted to evaluate the effect of eye tracking based feedback/training on lung nodule detection by assessing the interpretation performance of radiographers. These researchers have provided tailored feedback using eye tracking data from the participant (expert or novice) and attempted to evaluate whether this eye-gaze based feedback had a positive impact on the participant’s performance. The feedback based on eye tracking technology proved to have a positive effect since significant improvements were found. However, no studies have been completed to test participants on their detection of a range of chest pathologies and with the involvement of training based on the eye tracking. Published guidelines and websites make recommendations about how to interpret a radiographic image. Often trainee reporting clinicians combine advice given in this guidance with a variety of recommended search techniques to form their own image interpretation search strategy. However, despite this, no optimal standardised systematic approach for chest image interpretation has been recommended using an evidence base. We are also not aware of any training tool which uses eye tracking technology to communicate effective search strategies to trainees.
LanguageEnglish
Title of host publicationUnknown Host Publication
PublisherElsevier
Number of pages3
Publication statusAccepted/In press - 1 Mar 2017
EventEuropean Congress of Radiology - Vienna
Duration: 1 Mar 2017 → …

Conference

ConferenceEuropean Congress of Radiology
Period1/03/17 → …

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Keywords

  • chest reporting
  • eye tracking
  • training tool

Cite this

Mclaughlin, L., Bond, RR., Hughes, C., McConnell, J., Woznitza, N., Elsayed, A., ... McFadden, S. (Accepted/In press). Development of a digital platform to aid chest radiographic image interpretation. In Unknown Host Publication Elsevier.
Mclaughlin, Laura ; Bond, RR ; Hughes, Ciara ; McConnell, Jonathan ; Woznitza, Nick ; Elsayed, Ayman ; Cairns, Andrew ; Finlay, Derwar ; McFadden, Sonyia. / Development of a digital platform to aid chest radiographic image interpretation. Unknown Host Publication. Elsevier, 2017.
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abstract = "Training has been provided in a variety of methods and tested for its effect on image interpretation accuracy. Studies have attempted to evaluate the effect of eye tracking based feedback/training on lung nodule detection by assessing the interpretation performance of radiographers. These researchers have provided tailored feedback using eye tracking data from the participant (expert or novice) and attempted to evaluate whether this eye-gaze based feedback had a positive impact on the participant’s performance. The feedback based on eye tracking technology proved to have a positive effect since significant improvements were found. However, no studies have been completed to test participants on their detection of a range of chest pathologies and with the involvement of training based on the eye tracking. Published guidelines and websites make recommendations about how to interpret a radiographic image. Often trainee reporting clinicians combine advice given in this guidance with a variety of recommended search techniques to form their own image interpretation search strategy. However, despite this, no optimal standardised systematic approach for chest image interpretation has been recommended using an evidence base. We are also not aware of any training tool which uses eye tracking technology to communicate effective search strategies to trainees.",
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Mclaughlin, L, Bond, RR, Hughes, C, McConnell, J, Woznitza, N, Elsayed, A, Cairns, A, Finlay, D & McFadden, S 2017, Development of a digital platform to aid chest radiographic image interpretation. in Unknown Host Publication. Elsevier, European Congress of Radiology, 1/03/17.

Development of a digital platform to aid chest radiographic image interpretation. / Mclaughlin, Laura; Bond, RR; Hughes, Ciara; McConnell, Jonathan; Woznitza, Nick; Elsayed, Ayman; Cairns, Andrew; Finlay, Derwar; McFadden, Sonyia.

Unknown Host Publication. Elsevier, 2017.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Development of a digital platform to aid chest radiographic image interpretation

AU - Mclaughlin, Laura

AU - Bond, RR

AU - Hughes, Ciara

AU - McConnell, Jonathan

AU - Woznitza, Nick

AU - Elsayed, Ayman

AU - Cairns, Andrew

AU - Finlay, Derwar

AU - McFadden, Sonyia

PY - 2017/3/1

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N2 - Training has been provided in a variety of methods and tested for its effect on image interpretation accuracy. Studies have attempted to evaluate the effect of eye tracking based feedback/training on lung nodule detection by assessing the interpretation performance of radiographers. These researchers have provided tailored feedback using eye tracking data from the participant (expert or novice) and attempted to evaluate whether this eye-gaze based feedback had a positive impact on the participant’s performance. The feedback based on eye tracking technology proved to have a positive effect since significant improvements were found. However, no studies have been completed to test participants on their detection of a range of chest pathologies and with the involvement of training based on the eye tracking. Published guidelines and websites make recommendations about how to interpret a radiographic image. Often trainee reporting clinicians combine advice given in this guidance with a variety of recommended search techniques to form their own image interpretation search strategy. However, despite this, no optimal standardised systematic approach for chest image interpretation has been recommended using an evidence base. We are also not aware of any training tool which uses eye tracking technology to communicate effective search strategies to trainees.

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Mclaughlin L, Bond RR, Hughes C, McConnell J, Woznitza N, Elsayed A et al. Development of a digital platform to aid chest radiographic image interpretation. In Unknown Host Publication. Elsevier. 2017