we must attend to the object. So to find a specific object, we must search. Wolfe, J. M., & Bennett, S. C. (1997). Preattentive Object Files: Shapeless bundles of basic features. Vision Research, 37(1), 25-43.
of many error in medical image perception. Nodine, C. F., Mello-Thoms, C., Weinstein, S. P., Kundel, H. L., Conant, E. F., Heller-Savoy, R. E., et al. (2001). Blinded review of retrospectively visible unreported breast cancers: an eye-position analysis. Radiology, 221(1), 122-129. 20-30% Miss errors
Resident Expert Kundel, H. L., & La Follette, P. S., Jr. (1972). Visual search patterns and experience with radiological images. Radiology, 103(3), 523- 528. Kundel, H., L. . (2007). How to minimize perceptual error and maximize expertise in medical imaging. Paper presented at the Medical Imaging 2007: Image Perception, Observer Performance, and Technology Assessment. Random
Yes No Yes No No* No* *I say….Others would argue. (They are wrong….probably) Yes Wolfe, J. M., & Horowitz, T. S. (2004). What attributes guide the deployment of visual attention and how do they do it? Nature Reviews Neuroscience, 5(6), 495-501.
N., Kuzmova, Y., & Wolfe, J. M. (2010). Color Channels, not Color Appearance or Color Categories, Guide Visual Search for Desaturated Color Targets. Psychol Sci, 21(9), 1208-1214. Pink/peach/skin(?) is much faster than pale blue or green
data to answer that yet. Drew, T., Vo, M. L.-H., Olwal, A., Jacobson, F., Seltzer, S. E., & Wolfe, J. M. (2013). Scanners and drillers: Characterizing expert visual search through volumetric images. Journal of Vision, 13(10).
that they, too, use the human search engine Drew, T., Vo, M. L.-H., & Wolfe, J. M. (2013). The Invisible Gorilla Strikes Again: Sustained Inattentional Blindness in Expert Observers. Psychological Science, 24(9), 1848–1853.
0.8 1.0 250 500 750 1000 2000 And here are the results Flash duration (msec) False Alarm Rate Hit Rate Evans, K., Georgian-Smith, D., Tambouret, R., Birdwell, R., & Wolfe, J. (2013). The gist of the abnormal: Above-chance medical decision making in the blink of an eye. Psychonomic Bulletin & Review, 1-6.
inserted into normal workflow over the course of 9 months during which another 9826 other cases were screened. Estimated prevalence 0.8%. Data are the call back decisions. High Prevalence 100 cases (50 positive, 50 negative) each read by six radiologists (6 of 14 from the low prevalence arm). Prevalence is 50%. Reading the 100 cases took 3 hours. Data are the call back decisions and a 0-10 rating from negative to clearly abnormal.
low prevalence False alarm rates are somewhat lower at low prevalence Evans, K. K., Birdwell, R. L., & Wolfe, J. M. (2013). If You Don’t Find It Often, You Often Don’t Find It: Why Some Cancers Are Missed in Breast Cancer Screening. . PLoS ONE 8(5): e64366
benefit would be greater if CADe were used more effectively, We have shown that radiologists only recognize a correct CADe prompt 30% of the time (Nishikawa, 2012). “ Nishikawa, R. M., Schmidt, R. A., Linver, M. N., Edwards, A. V., Papaioannou, J., & Stull, M. A. (2012). Clinically missed cancer: how effectively can radiologists use computer-aided detection? AJR Am J Roentgenol, 198(3), 708-716.