Reader behavior in a detection task using single- and multislice image datasets

We assess human reader behavior such as reading times and browsing trends in a signal detection experiment with synthetic single-slice (ss) and multi-slice (ms) image datasets of varying task complexity, defined in this study as the ratio of the background lump size to the signal width. Three dataset types were generated by inserting one 3D Gaussian target of fixed size into the center of 3D volumes of correlated Gaussian noise with three different kernel sizes. Corresponding signal intensities were determined separately for the three background types using the staircase method targeting an AUC of 0.7 for ss datasets. Non-expert human readers were presented with ss (central slice of the volume) and ms datasets (slice-by-slice viewing in a stack-browsing mode). Readers were aware of the target's approximate location within the slice or volume. Readers could scroll freely through the ms datasets at arbitrary speed and direction with no time limit. Experiments were conducted in a controlled viewing environment on a 5MP digital mammography display. AUCs were 0.68-0.73 for ss; 0.82-0.98 for ms datasets. Reading time (ms, ss), the number of repetitions through the stack (ms), and the average number of slices per repetition (ms) were assessed. Browsing speeds were in the range of 1-7 slices per second. Results show that readers spent the shortest time and fewest repetitions reading TP cases, with FP and FN cases requiring the most attention. The reported trends concur with earlier chest x-ray and mammography studies which report that readers fixate longer on regions subsequently rated incorrectly.