A hybrid classifier for mass classification with different kinds of features in mammographyPaper presented at the 2nd international conference on Fuzzy Systems and Knowledge Discovery (FSKD 2005)
Date of this Version8-29-2005
Document TypeConference Paper
AbstractThis paper proposes a hybrid system which combines computer extracted features and human interpreted features from the mammogram, with the statistical classifier’s output as another kind of feature in conjunction with a genetic neural network classifier. The hybrid system produced better results than the single statistical classifier and neural network. The highest classification rate reached 91.3%. The area value under the ROC curve is 0.962. The results indicated that the mixed features contribute greatly for the classification of mass patterns into benign and malignant.
Citation InformationPing Zhang, Kuldeep Kumar and Brijesh Verma. "A hybrid classifier for mass classification with different kinds of features in mammography" Paper presented at the 2nd international conference on Fuzzy Systems and Knowledge Discovery (FSKD 2005) (2005)
Available at: http://works.bepress.com/kuldeep_kumar/24/