The goal of this study was to assess the effect of independent combination of multiple readers in mammography on detection performance, using different rules to combine localized observer responses. A group of 12 radiologists each read a series of 192 screening mammograms, including 96 prior mammograms of breast cancer cases in which a visible sign of abnormality could be identifed in retrospect. The other 96 cases were normal. In total the 12 readers annotated 1890 findings. LROC analysis was used to measure performance. The mean sensitivity in a false positive interval from 2 to 8% was 31.4% for single reading (range: 14.4% - 46.9%). The best rule for combination of observer scores was taking the average of all radiologists, using a zero score for radiologists who did not annotate the finding. With this strategy the average performance of 2 readers combined, in the interval selected, went up to 42.2%. When the interpretations of more readers were independently combined the mean sensitivity further increased, up to a level of 64.8% for the combination of all 12 readers. Using the mean score of only those readers who reported a finding turned out to be a poor strategy, yielding results that were similar or worse than single reading.
Digitization and CRT display reduce sharpness of mammograms. To ensure image quality on a CRT, comparable to the quality of original films, a modified unsharp-masking (USM) algorithm is proposed to correct for this reduction. This study evaluates the clinical value of this algorithm and determines the optimal setting of its parameters. Eight complete mammographic cases were processed by a modified USM algorithm with 19 settings for three parameters, resulting in 152 stimuli. All cases showed a clearly visible mass; five also contained microcalcifications. The modification of the standard USM algorithm consisted of selectively improving low contrasts. Moreover, the USM enhancement was made grey value dependent to avoid clipping. Four experienced screening radiologists and four physicists (having experience with mammography imaging) rated all mammograms on a 1-10 point scale, according to image quality and suitability for diagnosis. The images were randomly presented. Before the experiment started, a subset of the images was shown to familiarize the observers to the range of images and parameter settings. For a contrast enhancement factor of about 0.4, the processed mammograms appeared to be significantly better than the original digitized mammograms (P<.001). Differences in the results for the radiologists and the physicists were small.