Comparison of Multiple View Strategies to Reduce False Positives in Breast Imaging
IWDM '08 Proceedings of the 9th international workshop on Digital Mammography
Computer-aided evaluation of screening mammograms based on local texture models
IEEE Transactions on Image Processing
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Systems for computer aided detection of masses may be used more effectively when they are used for interpretation of suspect abnormalities, instead of solely using them as a prompting aid to avoid oversights. To use CAD algorithms for detection of masses as a decision aid it may be helpful to display suspiciousness of regions computed by CAD. In this paper the quality of probabilities computed for masses by a commercial CAD system is studied in two ways: 1) by comparing standalone performance of the system to that of experienced screening radiologists, and 2) by determining results of independent double reading with CAD. The study involves results of 15 readers who each read 500 mammograms, and two releases of the CAD algorithm. Independent double reading results are obtained by combining probabilities of the CAD system with the reader assessment for each localized finding reported by the reader, and by computing the fraction of cancers localized correctly as a function of false positive referrals. It was found that standalone performance of CAD is less than that of any reader in the study. Nevertheless, it was found that performance improves significantly with independent CAD reading, and that use of an improved CAD algorithm lead to significantly better results of the combined reader with CAD.