Nature of expertise in searching mammograms for breast masses

Eye position of observes representing four levels of training and experience: mammographers; mammography residents; mammographic technologists; and, laypersons were compared to a random search model as they examined a set of nine two-view digital mammogram pairs for breast masses. Analysis of time-to-hit data revealed that mammographers' training and experience combined to produce the most efficient search patterns as measured by the fastest search times to detect breast masses on two views. Scanning patterns of mammography residents and mammographic technologists were less efficient due to wider dispersion of visual attention that was divided between potential breast masses and perturbations in breast parenchyma. Because laypersons lacked training in radiology, bright blobs in the breast image were considered to be intuitively valid target candidates, and these features distracted search by capturing visual attention.