期刊
APPLIED SOFT COMPUTING
卷 43, 期 -, 页码 546-552出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.asoc.2016.03.003
关键词
Mammograms; Wave atom transform; SVM; k-NN; Sensitivity; Specificity; f-Measure
This paper presents an approach for breast cancer diagnosis in digital mammograms using wave atom transform. Wave atom is a recent member of the multi-resolution representation methods. Primarily, the mammogram images are decomposed on the basis of wave atoms, and then a special set of the biggest coefficients from wave atom transform is used as a feature vector. Two different classifiers, support vector machine and k-nearest neighbors, are employed to classify mammograms. The method is tested using two different sets of images provided by MIAS and DDSM database. (C) 2016 Elsevier B.V. All rights reserved.
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