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Observer performance evaluation of a method of simulating abnormalities in mammograms

The purpose of this study was to evaluate a method of creating synthetic normal and abnormal mammograms. Images consisting of 1024 x 1024 regions were extracted from digitized mammograms. Twenty-five regions included a single microcalcification cluster. A second set of twenty-five regions without calcifications was also selected. Calcifications were digitally removed by application of a median filter to form a third set of images. Finally, extracted calcifications were superposed on normal images to create a fourth set. Three mammographers evaluated the quality of the simulations. Their task was to classify the images according to real or simulated status using a 10-point rating scale. The classification accuracy was calculated by Receiver Operating Characteristic (ROC) analysis. Two other radiologists performed a paired image task on a subset of the images. They attempted to discriminate between real and simulated images that were simultaneously displayed, which was analyzed by a forced-choice method. In either case it was found that the probability of correct classification was insignificantly different from the chance level. We conclude that the simulation methodology employed was satisfactory. The ability to create synthetic images, that are indistinguishable from real images, is expected to facilitate modality evaluation studies in mammography.