DCT Based Features for the Detection of Microcalcifications in Digital Mammograms

A.B. Farag, Samia A. Mashali · 2006

In this paper, a set of spectral domain features based on the discrete cosine transform DCT of mammograms are extracted from the X-ray image, the extracted features by the proposed methods are exploited to classify regions of interest ROIs into positive ROIs containing clustered microcalcifications and negative ROIs containing normal tissues. A three-layer back-propagation neural network is used as a classifier, the results of the neural network for the extracted features are evaluated by using a receiver operation characteristics ROC analysis, the proposed technique is shown to be superior to the conventional methods with respect to classification accuracy and computational complexity

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