Abstract
The objective of the study was to assess the potential of a CAD device with computer aided classification capabilities to reduce interventional procedures for BI-RADS category 4A lesions. 113 such lesions (17 masses, 96 clusters), forwarded for biopsy (103 benign) were analyzed retrospectively by a CAD device that generated descriptors. The device extracted quantitative features characterizing the lesions by shape, margins, size and distribution. Descriptors taken from the BI-RADS lexicon for the appearance of the lesion were generated based on the values of the quantitative features. A paradigm based on the computer generated descriptors was developed to assist in assigning a level of suspicion. The paradigm deemed malignant, all 10 malignant cases of the study (100% sensitivity) and correctly classified 38 of the 103 benign lesions. The CAD-generated descriptors, thus, eliminated 36.9% of unnecessary biopsies without decreasing the sensitivity.
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Isaac, L., Richard, L., Shalom, B., Yossi, S., Philippe, B., Fanny, S. (2006). Computerized Classification Can Reduce Unnecessary Biopsies in BI-RADS Category 4A Lesions. In: Astley, S.M., Brady, M., Rose, C., Zwiggelaar, R. (eds) Digital Mammography. IWDM 2006. Lecture Notes in Computer Science, vol 4046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11783237_11
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DOI: https://doi.org/10.1007/11783237_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35625-7
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