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|Title: ||Method for tracking eye gaze during interpretation of endoluminal 3D CT colonography: technical description and proposed metrics for analysis|
|Authors: ||Phillips, Peter|
Taylor, Stuart A.
Altman, Douglas G.
Gale, Alastair G.
|Issue Date: ||2013|
|Publisher: ||© Radiological Society of North America|
|Citation: ||PHILLIPS, P. ... et al, 2013. Method for tracking eye gaze during interpretation of endoluminal 3D CT colonography: technical description and proposed metrics for analysis. Radiology, 267 (3), pp. 924 - 931|
|Abstract: ||Purpose: To develop an eye-tracking method applicable to three-dimensional (3D) images, where the abnormality is both moving and changing in size. Materials and Methods: Research ethics committee approval was granted to record eye-tracking data from six inexperienced readers who inspected eight short (<30 seconds) endoluminal fly-through videos extracted from computed tomographic (CT) colonography examinations. Cases included true-positive and false-positive polyp detections from a previous study (polyp diameters, 5-25 mm). Eye tracking was performed with a desk-mounted tracker, and readers indicated when they saw a polyp with a mouse click. The polyp location on each video frame was quantified subsequently by using a circular mask. Gaze data related to each video frame were calculated relative to the visible polyp boundary and used to identify eye movements that pursue a polyp target as it changes size and position during fly-through. Gaze data were then related to positive polyp detections by readers. Results: Tracking eye gaze on moving 3D images was technically feasible. Gaze was successfully classified by using pursuit analysis, and pursuit-based gaze metrics were able to help discriminate different reader search behaviors and methods of allocating visual attention during polyp identification. Of a total of 16 perceptual errors, 15 were recognition errors. There was only one visual search error. The largest polyp (25 mm) was seen but not recognized by five of six readers. Conclusion: Tracking a reader's gaze during endoluminal interpretation of 3D data sets is technically feasible and can be described with pursuit-based metrics. Perceptual errors can be classified into visual search errors and recognition errors. Recognition errors are more frequent in inexperienced readers. © RSNA, 2013.|
|Description: ||This article is closed access, it was published in the journal Radiology [© Radiological Society of North America]. The definitive version is available at: http://dx.doi.org/10.1148/radiol.12120062|
|Version: ||Accepted for publication|
|Publisher Link: ||http://dx.doi.org/10.1148/radiol.12120062|
|Appears in Collections:||Closed Access (Computer Science)|
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