Visual Search Performance and Strategy for Three-Dimensional Visualization Systems: Impact of Radiologist Experience
Source abstract
Abstract
The visual search performance of radiologists is systematically challenged due to the use of flat-panel displays when viewing multi-slice images. Three-dimensional visualization of information is expected to facilitate visual search for radiologists. However, as the differences in user performance, depending on radiologist experience, have not yet been assessed for real three-dimensional images, it is difficult to estimate the usability of new visualization systems for radiologists with different amounts of professional search experience. In this study, we aimed to determine how three-dimensional visual search is affected by radiologist experience and the physical properties of stimuli. Radiologists, residents, and medical students accomplished visual search tasks with varying set sizes and target-distractor similarities. Search items were presented on multiple display planes and image manipulation was conducted using a computer keyboard. We compared the search outcome and strategy among three groups of participants. All three groups submitted a similar number of correct responses depending on target-distractor similarity. However, in contrast to radiologists and residents, it took a considerably longer time for students to find the targets. The major differences were evident in search strategy when comparing the image manipulations of radiologists with those of residents and students. Our results demonstrated that experienced radiologists’ search performance benefited from seeing the entire three-dimensional view of an image, whereas residents and students focused instead on reducing the amount of information and searched in a selective manner. These findings should be taken into account when planning the implementation of new workstations with three-dimensional visualization in radiology.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Radiology practices and education · Digital Imaging in Medicine · Digital Radiography and Breast Imaging
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Optometry and Vision Science, Faculty of Physics, Mathematics and Optometry, University of Latvia, Jelgavas 1, LV-1004 Riga, Latvia
Laboratory of Statistical Research and Data Analysis, Faculty of Physics, Mathematics and Optometry, University of Latvia, Jelgavas 3, LV-1004 Riga, Latvia
Faculty of Medicine, Riga Stradiņš University, Dzirciema 16, LV-1007 Riga, Latvia
Funding
Latvijas Universitate · LightSpace Technologies
References (55)
Show source-provided references
1. Optimizing analysis, visualization, and navigation of large image data sets: One 5000-section CT scan can ruin your whole day10.1148/radiol.11091276 ↗
2. Scanners and drillers: Characterizing expert visual search through volumetric images10.1167/13.10.3 ↗
3. Volumetric CT-images improve testing of radiological image interpretation skills10.1016/j.ejrad.2014.12.015 ↗
4. Analysis of visual search behaviour from experienced radiologists interpreting digital breast tomosynthesis (DBT) images: A pilot study
5. Current perspectives in medical image perception10.3758/APP.72.5.1205 ↗
6. Channelized Hotelling observer correlation with human observers for low-contrast detection in liver CT images
7. Capacity limits and how the visual system copes with them
8. Medical students’ cognitive load in volumetric image interpretation: Insights from human-computer interaction and eye movements10.1016/j.chb.2016.04.015 ↗
9. Effects of information accuracy and volume on decision making10.1080/08995605.2018.1425586 ↗
10. Comparison of digital mammography alone and digital mammography plus tomosynthesis in a population-based screening program10.1148/radiol.12121373 ↗
11. Mental fatigue caused by prolonged cognitive load asociated with sympathetic hyperactivity10.1186/1744-9081-7-17 ↗
12. Mental fatigue affects visual attention10.1371/journal.pone.0048073 ↗
13. Augmented virtual reality assisted treatment planning for splenic artery aneurysms: A pilot study10.1016/j.jvir.2018.01.037 ↗
14. Evaluation of virtual reality for detection of lung nodules on computed tomography10.18383/j.tom.2018.00053 ↗
15. Implementing virtual and augmented reality tools for radiology education and training, communication, and clinical care10.1148/radiol.2019182210 ↗
16. Mohamudally, N. (2018). Augmented reality and virtual reality: Initial successes in diagnostic radiology. State of the Art Virtual Reality and Augmented Reality Knowhow, IntechOpen.10.5772/intechopen.71232 ↗
17. Krupinski, E.A. (2008). Stereoscopic digital mammography: Improved accuracy of lesion detection in breast cancer screening. Digital Mammography, Springer. IWDM 2008, Lecture Notes in Computer Science 5116.10.1007/978-3-540-70538-3 ↗
18. Stereoscopic digital mammogram: Usefulness in daily practice10.1016/j.jogoh.2018.03.009 ↗
19. Volumetric 3D displays and application infrastructure10.1109/MC.2005.276 ↗
20. Real-time volumetric 3D imaging technology
21. Vergence-accommodation conflicts hinder visual performance and cause visual fatigue10.1167/8.3.33 ↗
22. Zabels, R., Osmanis, K., Narels, M., Gertners, U., Ozols, A., Rutenbergs, K., and Osmanis, I. (2019). AR displays: Next-generation technologies to solve the vergence-accommodation conflict. Appl. Sci., 9.10.3390/app9153147 ↗
23. Volumetric displays: Turning 3D inside-out10.1364/OPN.29.6.000026 ↗
24. A review of existing and potential computer user interfaces for modern radiology10.1007/s13244-018-0620-7 ↗
25. Jackie, J.A. (2012). Visual displays. Human Computer Interaction Handbook: Fundamentals, Evolving Technologies, and Emerging Application, CRC Press. [3rd ed.].
26. Clark, K. (2014). Variation in Visual Search Abilities and Performance. [Ph.D. Thesis, Duke University].
27. How do radiologists use the human search engine?10.1093/rpd/ncv501 ↗
28. Perceptual learning of the detection of features in X-ray images: A functional role for improvements in adults’ visual sensitivity?10.1037/0096-1523.26.1.379 ↗
29. The development of expertise in radiology: In chest radiograph interpretation, “expert” search pattern may predate “expert” levels of diagnostic accuracy for pneumothorax identification10.1148/radiol.2016150409 ↗
30. Radiology image perception and observer performance: How does expertise and clinical information alter interpretation? Stroke detection explored through eye-tracking
31. Inversion effects in the expert classification of mammograms and faces10.1186/s41235-018-0123-6 ↗
32. Individual differences in perceptual abilities in medical imaging: The Vanderbilt Chest Radiograph Test10.1186/s41235-017-0073-4 ↗
33. The radiologist’s gaze: Mapping three-dimensional visual search in computed tomography of the abdomen and pelvis10.1007/s10278-018-0121-8 ↗
34. What is different about a radiologist’s brain?10.1148/radiol.2363041370 ↗
35. Experimental system for measurement of radiologists’ performance by visual search task10.1186/2193-1801-2-607 ↗
36. Visual search of experts in medical image reading: The effect of training, target prevalence, and expert knowledge10.3389/fpsyg.2013.00166 ↗
37. Spatial perception testing in diagnostic radiology10.2214/ajr.143.5.1105 ↗
38. Perceptual skill, radiology expertise, and visual test performance with NINA and WALDO10.1016/S1076-6332(98)80295-X ↗
39. Evaluating different radiology workstation interaction techniques with radiologists and laypersons10.1007/s10278-004-2192-y ↗
40. Influence of radiology expertise on the perception of nonmedical images
41. The holistic processing account of visual expertise in medical image perception: A review10.3389/fpsyg.2017.01620 ↗
42. An application of eyegaze tracking for designing radiologists’ workstations: Insights for comparative visual search tasks10.1145/1141897.1141902 ↗
43. Eye-tracking of nodule detection in lung CT volumetric data10.1118/1.4919849 ↗
44. Radiologists’ eye gaze when reading cranial CT images
45. Volumetric image interpretation in radiology: Scroll behavior and cognitive processes10.1007/s10459-018-9828-z ↗
46. Advanced multiplanar volumetric 3d display
47. Exploring the effect of context and expertise on attention: Is attention shifted by information in medical images?10.3758/s13414-019-01695-7 ↗
48. Peripheral vision and oculomotor control during visual search10.1016/S0042-6989(98)00213-2 ↗
49. Visual search performance on an LCD monitor: Effects of color combination of figure and icon background, shape of icon, and line width of icon border10.2466/pms.104.2.562-574 ↗
50. Becker, S.I. (2011). Determinants of dwell time in visual search: Similarity or perceptual difficulty?. PLoS ONE, 6.10.1371/journal.pone.0017740 ↗
51. The effects of target location and target distinction on visual search in a depth display10.1007/s10845-009-0280-z ↗
52. Eye movements and attention in visual feature search with graded target-distractor-similarity10.16910/jemr.3.1.4 ↗
53. Looking in the same manner but seeing it differently: Bottom-up and expertise effects in radiology10.1002/acp.2886 ↗
54. Interactions of perceptual and conceptual processing: Expertise in medical image diagnosis10.1016/j.ijhcs.2007.11.004 ↗
55. What can you see in a single glance and how might this guide visual search in medical images?10.1148/rg.331125023 ↗