Limiting Level of False-Positive Detections in Classification of Microcalcification Clusters in Mammograms

The presence of false positives (FPs) in detection of clustered microcalcifications (MCs) in mammograms can negatively affect the performance in computer-aided diagnosis (CADx) for breast cancer. The level of FPs is typically controlled in a trade-off with the detection sensitivity by an operating p...

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Bibliographic Details
Main Authors: Sainz de Cea, Maria V., Nishikawa, Robert M., Yang, Yongyi
Format: Conference Proceeding
Language:English
Subjects:
Breast cancer
Cancer
clustered microcalcifications
computer aided diagnosis
Detectors
Feature extraction
Lesions
Mammography
Sensitivity
Support vector machines
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Summary:The presence of false positives (FPs) in detection of clustered microcalcifications (MCs) in mammograms can negatively affect the performance in computer-aided diagnosis (CADx) for breast cancer. The level of FPs is typically controlled in a trade-off with the detection sensitivity by an operating point in detection. However, due to inter-patient variability, the occurrence of FPs can become exceedingly high among some cases when the operating point is set at a reasonable sensitivity level. We propose a strategy for automatically limiting the level of FP detections on a case-by-case basis. We first estimate the number of FPs among the detected MCs in a given lesion, then adjust the operating point if the FP fraction is determined to exceed an allowance level. We demonstrated this strategy on a set of 188 FFDM images. The results show that it can lead a significant improvement in accuracy in differentiating MC lesions as being benign or malignant based on the detected MCs.
ISSN:1945-8452
DOI:10.1109/ISBI.2019.8759552