Characteristics of expert search behavior in volumetric medical image interpretation

Lauren H. Williams*, Ann J. Carrigan, Megan Mills, William F. Auffermann, Anina N. Rich, Trafton Drew

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)
17 Downloads (Pure)


Purpose: Experienced radiologists have enhanced global processing ability relative to novices, allowing experts to rapidly detect medical abnormalities without performing an exhaustive search. However, evidence for global processing models is primarily limited to two-dimensional image interpretation, and it is unclear whether these findings generalize to volumetric images, which are widely used in clinical practice. We examined whether radiologists searching volumetric images use methods consistent with global processing models of expertise. In addition, we investigated whether search strategy (scanning/drilling) differs with experience level. 

Approach: Fifty radiologists with a wide range of experience evaluated chest computed-tomography scans for lung nodules while their eye movements and scrolling behaviors were tracked. Multiple linear regressions were used to determine: (1) how search behaviors differed with years of experience and the number of chest CTs evaluated per week and (2) which search behaviors predicted better performance. 

Results: Contrary to global processing models based on 2D images, experience was unrelated to measures of global processing (saccadic amplitude, coverage, time to first fixation, search time, and depth passes) in this task. Drilling behavior was associated with better accuracy than scanning behavior when controlling for observer experience. Greater image coverage was a strong predictor of task accuracy. 

Conclusions: Global processing ability may play a relatively small role in volumetric image interpretation, where global scene statistics are not available to radiologists in a single glance. Rather, in volumetric images, it may be more important to engage in search strategies that support a more thorough search of the image.

Original languageEnglish
Article number041208
Pages (from-to) 041208-1- 041208-24
Number of pages24
JournalJournal of Medical Imaging
Issue number4
Publication statusPublished - 14 Jul 2021


  • medical image perception
  • gist processing
  • expertise
  • scanners and drillers
  • lung cancer detection


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