an enhanced decision support system for breast tumor identification in screening mammograms using combined classifier
An enhanced Computer Aided Clinical Decision Making System using Multiple classifier systems (MCSs) based on the combination of a set of different classifiers for classifying the breast tumor as malignant and benign has been developed and presented in this paper. The Multilayer Back Propagation Neural Network (MBPN), Radial-Basis-Function Neural Network (RBFNN), Asymmetrical Support Vector Machine (ASVM) and combined classifier with major voting method, behaviour-knowledge space method have been used to classify the tumor. The multiple features with optimal feature selection and combined classifier with behaviour-knowledge space method is found to have the accuracy 99.97\%. The performance of the proposed clinical decision support system has been estimated and found that this hybrid system will provide valuable information to the physicians in clinical pathology.
breast tumors mammogram combined classifier rbfnn asvm multilayer back propagation network feature extraction image denoising and enhancement