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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 and McFadden, S. L. (2017) The use of eye tracking technology to assess the interpretation of radiographic images. In: UKRC, Manchester. Supplement to BJR. 3 pp. [Conference contribution]

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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.

Item Type:Conference contribution (Paper)
Keywords:radiography, eye tracking, interpretation, musculoskeletal, chest
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Faculty of Life and Health Sciences
Faculty of Life and Health Sciences > School of Health Sciences
Research Institutes and Groups:Institute of Nursing and Health Research > Centre for Health and Rehabilitation Technologies
Institute of Nursing and Health Research
Computer Science Research Institute > Smart Environments
Computer Science Research Institute
ID Code:38642
Deposited By: Dr Sonyia McFadden
Deposited On:24 Apr 2018 12:56
Last Modified:24 Apr 2018 12:56

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