Extracting ROIs in Mammograms Using ICA

In order to preprocess mammograms for diagnosing the early cases of breast cancer and improve the computational efficiency in the computer-aided detection of micro-calcifications in mammograms,this paper presents a new method based on independent component analysis(ICA),which can extract the region of interests(ROI) automatically.The proposed method is based on a four-step procedure:(1) the mammogram was divided into sub-images of the same size as the pending ROI;(2) the base images were obtained by applying ICA to ROI;(3) the feature vector was extracted by projecting the pending ROI to subspace that is composed of the base images;(4) artificial neural network(ANN) was used to recognize ROI.The method was adopted in the processing of the test samples with a true positive rate(TPR) of 91%.The proposed method was easy to use,effective,and with higher intelligence,which provided a new idea for automatic ROI extraction.