Although there is an existing literature devoted to understanding search strategies in 2-D medical images such as chest radiographs (Berbaum et al.,
1998; Ellis et al.,
2006; Kundel, Nodine, & Carmody,
1977,
1978; Kundel, Nodine, & Krupinski,
1989; Kundel, Nodine, Thickman, & Toto,
1987; Kundel, Nodine, & Toto,
1991; Manning, Barker-Mill, Donovan, & Crawford,
2006) and mammograms (Krupinski,
1996; Krupinski & Nishikawa,
1997; Kundel, Nodine, Conant, & Weinstein,
2007; Mello-Thoms, Dunn, Nodine, & Kundel,
2001; Mello-Thoms, Dunn, Nodine, Kundel, & Weinstein,
2002), much less is known about how search is accomplished through 3-D chest CT scans, or about 3-D search strategies more generally. A limited number of studies have examined visual search while moving through depth outside of the medical setting (Smith et al.,
2008; Smith, Hood, & Gilchrist,
2010; Solman, Cheyne, & Smilek,
2012; Solman, Wu, Cheyne, & Smilek,
2013). Some studies have used eye-tracking to examine search strategy in CT colonography (Phillips et al.,
2008) and stroke diagnosis in head CT scans (Cooper, Gale, Darker, Toms, & Saada,
2009; Cooper et al.,
2010). These studies have predominantly focused on difference between 2-D and 3-D search, as well as the role of expertise. Thus far, these studies of search through volumetric images seems to conform to the general findings in the 2-D medical image literature (e.g., Manning, Ethell, Donovan, & Crawford,
2006): Experts tend to be much more efficient in their eye-movement patterns, while novices seem to follow a haphazard pattern of search.