The use of eye tracking technology to assess the interpretation of radiographic images

Laura McLaughlin, RR Bond, Ciara Hughes, J McConnell, N Woznitza, A Elsayad, A Cairns, D Finlay, S. L. McFadden

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

Abstract

Background:Studies have used eye tracking technology to assess the radiographer’s ability to identify pulmonary lung nodules within chest images. Eye tracking technology has provided an insight into the cognitive processes during image interpretation. Within this study we use eye tracking technology to assess image interpretation skills between various levels of experience in radiography and on a variety of pathologies.Method:Eye tracking data was collected using the Tobii X60 eye tracker during participant interpretation of 8 radiographic images including the MSK system and chest. A total of 464 image interpretations were collected. Participants consisted of 21 radiography students, 19 qualified radiographers and 18 reporting radiographers. Results:Reporting radiographers demonstrated a 15% greater accuracy rate (p≤0.001), were more confident (p≤0.001) and took a mean of 2.4s longer to decide on image features compared to students. Reporting radiographers had a 15% greater accuracy rate (p≤0.001), were more confident (p≤0.001) and took longer to form an image diagnosis (p=0.02) than radiographers. Reporting radiographers had a greater mean fixation duration (p=0.01), mean fixation count (p=0.04) and mean visit count (p=0.04) within the areas of pathology compared to students but no significant difference (fixation duration p= ,fixation counts p= and fixation visits p= ) than radiographers. Conclusion:Eye gaze metrics were indicative of the radiographer’s competency. Participants’ thoughts and decisions were quantified using the eye tracking data. Eye tracking metrics also reflected the different search strategies that each group of participants adopted during their image interpretations.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages3
Publication statusAccepted/In press - 14 Jun 2017
EventUKRC - Manchester
Duration: 14 Jun 2017 → …

Conference

ConferenceUKRC
Period14/06/17 → …

Fingerprint

Technology
Students
Radiography
Thorax
Pathology
Lung

Keywords

  • radiography
  • eye tracking
  • interpretation
  • musculoskeletal
  • chest

Cite this

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title = "The use of eye tracking technology to assess the interpretation of radiographic images",
abstract = "Background:Studies have used eye tracking technology to assess the radiographer’s ability to identify pulmonary lung nodules within chest images. Eye tracking technology has provided an insight into the cognitive processes during image interpretation. Within this study we use eye tracking technology to assess image interpretation skills between various levels of experience in radiography and on a variety of pathologies.Method:Eye tracking data was collected using the Tobii X60 eye tracker during participant interpretation of 8 radiographic images including the MSK system and chest. A total of 464 image interpretations were collected. Participants consisted of 21 radiography students, 19 qualified radiographers and 18 reporting radiographers. Results:Reporting radiographers demonstrated a 15{\%} greater accuracy rate (p≤0.001), were more confident (p≤0.001) and took a mean of 2.4s longer to decide on image features compared to students. Reporting radiographers had a 15{\%} greater accuracy rate (p≤0.001), were more confident (p≤0.001) and took longer to form an image diagnosis (p=0.02) than radiographers. Reporting radiographers had a greater mean fixation duration (p=0.01), mean fixation count (p=0.04) and mean visit count (p=0.04) within the areas of pathology compared to students but no significant difference (fixation duration p= ,fixation counts p= and fixation visits p= ) than radiographers. Conclusion:Eye gaze metrics were indicative of the radiographer’s competency. Participants’ thoughts and decisions were quantified using the eye tracking data. Eye tracking metrics also reflected the different search strategies that each group of participants adopted during their image interpretations.",
keywords = "radiography, eye tracking, interpretation, musculoskeletal, chest",
author = "Laura McLaughlin and RR Bond and Ciara Hughes and J McConnell and N Woznitza and A Elsayad and A Cairns and D Finlay and McFadden, {S. L.}",
year = "2017",
month = "6",
day = "14",
language = "English",
booktitle = "Unknown Host Publication",

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McLaughlin, L, Bond, RR, Hughes, C, McConnell, J, Woznitza, N, Elsayad, A, Cairns, A, Finlay, D & McFadden, SL 2017, The use of eye tracking technology to assess the interpretation of radiographic images. in Unknown Host Publication. UKRC, 14/06/17.

The use of eye tracking technology to assess the interpretation of radiographic images. / McLaughlin, Laura; Bond, RR; Hughes, Ciara; McConnell, J; Woznitza, N; Elsayad, A; Cairns, A; Finlay, D; McFadden, S. L.

Unknown Host Publication. 2017.

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

TY - GEN

T1 - The use of eye tracking technology to assess the interpretation of radiographic images

AU - McLaughlin, Laura

AU - Bond, RR

AU - Hughes, Ciara

AU - McConnell, J

AU - Woznitza, N

AU - Elsayad, A

AU - Cairns, A

AU - Finlay, D

AU - McFadden, S. L.

PY - 2017/6/14

Y1 - 2017/6/14

N2 - Background:Studies have used eye tracking technology to assess the radiographer’s ability to identify pulmonary lung nodules within chest images. Eye tracking technology has provided an insight into the cognitive processes during image interpretation. Within this study we use eye tracking technology to assess image interpretation skills between various levels of experience in radiography and on a variety of pathologies.Method:Eye tracking data was collected using the Tobii X60 eye tracker during participant interpretation of 8 radiographic images including the MSK system and chest. A total of 464 image interpretations were collected. Participants consisted of 21 radiography students, 19 qualified radiographers and 18 reporting radiographers. Results:Reporting radiographers demonstrated a 15% greater accuracy rate (p≤0.001), were more confident (p≤0.001) and took a mean of 2.4s longer to decide on image features compared to students. Reporting radiographers had a 15% greater accuracy rate (p≤0.001), were more confident (p≤0.001) and took longer to form an image diagnosis (p=0.02) than radiographers. Reporting radiographers had a greater mean fixation duration (p=0.01), mean fixation count (p=0.04) and mean visit count (p=0.04) within the areas of pathology compared to students but no significant difference (fixation duration p= ,fixation counts p= and fixation visits p= ) than radiographers. Conclusion:Eye gaze metrics were indicative of the radiographer’s competency. Participants’ thoughts and decisions were quantified using the eye tracking data. Eye tracking metrics also reflected the different search strategies that each group of participants adopted during their image interpretations.

AB - Background:Studies have used eye tracking technology to assess the radiographer’s ability to identify pulmonary lung nodules within chest images. Eye tracking technology has provided an insight into the cognitive processes during image interpretation. Within this study we use eye tracking technology to assess image interpretation skills between various levels of experience in radiography and on a variety of pathologies.Method:Eye tracking data was collected using the Tobii X60 eye tracker during participant interpretation of 8 radiographic images including the MSK system and chest. A total of 464 image interpretations were collected. Participants consisted of 21 radiography students, 19 qualified radiographers and 18 reporting radiographers. Results:Reporting radiographers demonstrated a 15% greater accuracy rate (p≤0.001), were more confident (p≤0.001) and took a mean of 2.4s longer to decide on image features compared to students. Reporting radiographers had a 15% greater accuracy rate (p≤0.001), were more confident (p≤0.001) and took longer to form an image diagnosis (p=0.02) than radiographers. Reporting radiographers had a greater mean fixation duration (p=0.01), mean fixation count (p=0.04) and mean visit count (p=0.04) within the areas of pathology compared to students but no significant difference (fixation duration p= ,fixation counts p= and fixation visits p= ) than radiographers. Conclusion:Eye gaze metrics were indicative of the radiographer’s competency. Participants’ thoughts and decisions were quantified using the eye tracking data. Eye tracking metrics also reflected the different search strategies that each group of participants adopted during their image interpretations.

KW - radiography

KW - eye tracking

KW - interpretation

KW - musculoskeletal

KW - chest

M3 - Conference contribution

BT - Unknown Host Publication

ER -

McLaughlin L, Bond RR, Hughes C, McConnell J, Woznitza N, Elsayad A et al. The use of eye tracking technology to assess the interpretation of radiographic images. In Unknown Host Publication. 2017