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A new MicroCalcification clusters (MCs) detection method in mammograms is proposed, which is based on a new ensemble learning method. In this paper, the authors propose a bagging with adaptive cost adjustment ensemble algorithm; and a new ensemble strategy, called boosting with relevance feedback, by embedding the relevance feedback technique into the heterogenous base learner training, and meanwhile carefully design an effectively systematical feedback scheme, which promise the preventing of overfitting. The ground truth of MCs is assumed to be known as a priori.
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