Paper
20 March 2007 Evaluating user interfaces for stack mode viewing
M. Stella Atkins, Arthur E. Kirkpatrick, Adelle Knight, Bruce Forster
Author Affiliations +
Abstract
The goal of this research was to evaluate two different stack mode layouts for 3D medical images - a regular stack mode layout where just the topmost image was visible, and a new stack mode layout, which included the images just before and after the main image. We developed stripped down user interfaces to test the techniques, and designed a look-alike radiology task using 3D artificial target stimuli implanted in the slices of medical image volumes. The task required searching for targets and identifying the range of slices containing the targets. Eight naive students participated, using a within-subjects design. We measured the response time and accuracy of subjects using the two layouts and tracked the eyegaze of several subjects while they performed the task. Eyegaze data was divided into fixations and saccades Subjects were 19% slower with the new stack layout than the standard stack layout, but 5 of the 8 subjects preferred the new layout. Analysis of the eyegaze data showed that in the new technique, the context images on both sides were fixated once the target was found in the topmost image. We believe that the extra time was caused by the difficulty in controlling the rate of scrolling, causing overshooting. We surmise that providing some contextual detail such as adjacent slices in the new stack mode layout is helpful to reduce cognitive load for this radiology look-alike task.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Stella Atkins, Arthur E. Kirkpatrick, Adelle Knight, and Bruce Forster "Evaluating user interfaces for stack mode viewing", Proc. SPIE 6515, Medical Imaging 2007: Image Perception, Observer Performance, and Technology Assessment, 65150A (20 March 2007); https://doi.org/10.1117/12.707533
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Medical imaging

Radiology

3D image processing

Human-machine interfaces

Magnetic resonance imaging

3D acquisition

Eye

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