Title

A hybrid classifier for mass classification with different kinds of features in mammography

Date of this Version

8-29-2005

Document Type

Conference Paper

Publication Details

Interim status: Citation only.

Zhang, P., Kumar, K. and Verma, B. (2005). 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), Changsha, China.

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2005 HERDC submission.

© Copyright Springer, 2005

Abstract

This 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.

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This document has been peer reviewed.