Abstract
We evaluate a CAD device with detection and classification capabilities and compare conventional to computerized analysis. 243 cases (126 malignant, 117 benign) were analysed using BI-RADS and digitized (600 DPI, 12 bits). Lesions were detected, classified by likelihood of malignancy, and stratified into BI-RADS categories 2–5 by the CAD device. The falsely detected findings scored by CAD as low probability of malignancy were discarded to evaluate the true false positive rate. The CAD device sensitivity was 96% for masses and 95% for clusters of MCs. Malignancies were correctly classified by CAD in 95%. 67% of the false positive detected masses and 76% of the false positive clusters were classified benign by the CAD device, reducing the false positive rate per view from 0.59 to 0.20 for masses and from 0.30 to 0.07 for clusters. Conventional interpretation yielded a ROC Az of 0.76. CAD improved the Az to 0.88 (pO.OOl).
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© 2003 Springer-Verlag Berlin Heidelberg
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Fields, S. et al. (2003). Improved mammographic accuracy with CAD assisted classification of lesions. In: Peitgen, HO. (eds) Digital Mammography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59327-7_69
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DOI: https://doi.org/10.1007/978-3-642-59327-7_69
Publisher Name: Springer, Berlin, Heidelberg
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