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Computer-assisted perception aids pulmonary nodule detection

We have been monitoring the eye fixations of radiologists in order to identify why errors occur in the detection of pulmonary nodules. From these studies we have concluded that most errors are due not to overlooking, but to failure to report nodules that have been fixated by the eyes, often for prolonged gaze durations. Observers visually attend to the nodule, perhaps even apply decision criteria, but falsely decide that it is not the target of search. Because omission errors are associated with clusters of eye fixations having prolonged gaze durations, visual dwell can be used to predict the locations of potentially-missed nodules. A computer-assisted perception (CAP) algorithm has been developed to localize potential lung nodules based on measuring the durations of clusters of eye fixations during search for nodules. In an experiment to test the effectiveness of CAP, observers' eye-position was recorded during initial image reading. This was followed by CAP which consisted of playing back the highlighted locations of prolonged dwells indicating sites of potentially-missed nodules. The observers evaluated each CAP site for nodules and revised their initial decisions. For comparison, the same observers read the images a second time, after a two- month interval, without CAP in a counterbalanced design. The CAP condition resulted in a 16 percent increase in detection performance (AFROC) compared to the non-CAP condition.