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In this paper, classification of mammograms for breast cancer detection based on Discrete Curvelet Transform (DCT) and Multi-Layer Perceptron (MLP) is proposed. The mammogram patches are first filtered by Column wise neighborhood operations Filter (COLFILT). Enhanced patches are further decomposed into four sub-bands by using DCT. Dense Scale Invariant Feature Transform (DSIFT) method is use to extract the six rotation and scale invariant features for all the sub-bands. By using these sub-bandsfatcat:su6gaiisdbae3jjroyhxkyj2eq