Affordable Access

Radial basis functions-simulated annealing classification of mammographic calcifications.

Authors
Type
Published Article
Journal
Annual International Conference of the IEEE Engineering in Medicine and Biology Society
1557-170X
Publication Date
Volume
3
Pages
1644–1647
Identifiers
PMID: 17272017
Source
Medline

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.

There are no comments yet on this publication. Be the first to share your thoughts.

Statistics

Seen <100 times
0 Comments