title: Radial basis functions-simulated annealing classification of mammographic calcifications.
abstract: We investigated several approaches to classify mammographic calcifications as malignant or benign: a supervised classifier, multi-layer perceptron (MLP), a supervised and unsupervised classifier, a classifier based upon adaptive resonance theory with linear discriminant analysis (ART2LDA), and a classifier based upon nonlinear and combinational optimization techniques: RBF (radial basis functions)-simulated annealing. The classifiers were trained using shape factors extracted from 143 mammographic calcifications (79 malignant and 64 benign), adopting the leave-one-cut procedure. The classifiers' performance was compared in terms of the area under the ROC curve. The best result of 0.97 was obtained with RBF-simulated annealing, which was significantly better than the results obtained with MLP and ART2LDA, which were, respectively, 0.70 and 0.71.
authors.affiliation: Departamento de Engenharia de Sistemas Eletrônicos, São Paulo Universidade, Brazil.
authors.forename: Rafael
authors.initials: R
authors.lastname: do Espirito Santo
authors.forename: Roseli
authors.initials: R
authors.lastname: de Deus Lopes
authors.forename: Rangaraj
authors.initials: R
authors.lastname: Rangayyan