A comparison of visual identification of dental radiographic and nonradiographic images using eye tracking technology. Issue 1 (18th October 2019)

• Record Type: Journal Article
• Authors: Botelho, Michael G.; Ekambaram, Manikandan; Bhuyan, Sangeeta Y.; Yeung, Andy Wai Kan; Tanaka, Ray; Bornstein, Michael M.; Li, Kar Yan
• Is Part Of: Clinical and experimental dental research. Volume 6:Issue 1(2020)
• Page Start: 59
• Page End: 68
• Publication Date: 2019-10-18
• Subjects: eye tracking -- face recognition -- gaze analysis -- visual recognition; Dentistry -- Periodicals; Dentistry; Oral Medicine; Mouth Diseases; Dentistry; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 617.6
• DOI: 10.1002/cre2.249
• Languages: English
• ISSNs: 2057-4347

Abstract

Abstract: Objectives: Eye tracking has been used in medical radiology to understand observers' gaze patterns during radiological diagnosis. This study examines the visual identification ability of junior hospital dental officers (JHDOs) and dental surgery assistants (DSAs) in radiographic and nonradiographic images using eye tracking technology and examines if there is a correlation. Material and methods: Nine JHDOs and nine DSAs examined six radiographic images and 16 nonradiographic images using eye tracking. The areas of interest (AOIs) of the radiographic images were rated as easy, medium, and hard, and the nonradiographic images were categorized as pattern recognition, face recognition, and image comparison. The participants were required to identify and locate the AOIs. Data analysis of the two domains, entire slide and AOI, was conducted by evaluating the eye tracking metrics (ETM) and the performance outcomes. ETM consisted of six parameters, and performance outcomes consisted of four parameters. Results: No significant differences were observed for ETMs for JHDOs and DSAs for both radiographic and nonradiographic images. The JHDOs showed significantly higher percentage in identifying AOIs than DSAs for all the radiographic images (72.7% vs. 36.4%, p = .004) and for the easy categorization of radiographic AOIs (85.7% vs. 42.9%, p = .012). JHDOs with higher correct identification percentage in face recognition had a shorter dwell time in AOIs. Conclusions: Although no significant relation was observed between radiographic and nonradiographic images, there were some evidence that visual recognition skills may impact certain attributes of the visual search pattern in radiographic images.