Abnormalities Detection in Digital Mammography Using Template Matching

Breast cancer affects 1 in 8 women in the United States. Early detection and diagnosis is key to recovery. Computer-Aided Detection (CAD) of breast cancer helps decrease morbidity and mortality rates. In this study we apply Template Matching as a method for breast cancer detection to a novel data set comprised of mammograms annotated according to ground truth. Performance is evaluated in terms of Area Under the Receiver Operator Characteristic Curve (Area Under ROC) and Free-response ROC.

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