Comparison of eye position versus computer identified microcalcification clusters on mammograms.

The purpose of this study was to compare identifications of microcalcification clusters on mammograms by a computerized detection scheme and by human observers having their eye position recorded. Eighty digitized mammograms (half with a subtle microcalcification cluster) were analyzed by a computerized detection scheme and then were read from laser-printed films by six mammographers while eye position was recorded. The computer had 83% true positives with a false-positive rate of 0.5 per image. The true positives of the radiologists ranged from 78% to 90%, with false-positive rates ranging from 0.03 to 0.20. Locations of true and false positives identified by computer and by the human were compared. All but 5% of the true clusters were identified by either the computer, human, or by both. Here 10% of the clusters were detected by only the computer, and 11% were missed by the computer but detected by at least one radiologist. False positives were of three types: identified by computer only, by the human reader only, or by both. Eye-position data indicated significant differences in dwell time between both true-positive and false-positive locations reported by the radiologist versus the computer detections. A follow-up analysis indicated that microcalcification clusters and false positives were judged to have more identifiable characteristics of true calcifications and were associated with longer gaze durations than those with fewer microcalcification characteristics. In general, the computer was able to detect clusters judged to have few or no features that the radiologists were not able to detect. Comparison of computer versus human identification of microcalcification clusters may be useful for improving computerized detection schemes to serve as clinical aids to mammographers, and for understanding what image features lead to false-positive decisions for both the computer and the human reader.