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Feature selection and classification of breast cancer on dynamic Magnetic Resonance Imaging by using artificial neural networks

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5 Author(s)
Keivanfard, F. ; Electr. & Comput. Eng. Dept, KNT Univ. of Technol., Tehran, Iran ; Teshnehlab, M. ; Aliyari Shoorehdeli, M. ; Ke Nie
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In this paper, a new feature selection and classification methods based on artificial neural network are applied to classify breast cancer on dynamic Magnetic Resonance Imaging (MRI). The database including benign and malignant lesions is specified to select the features and classify with proposed methods. It is collected from 2004 to 2006. A forward selection method is applied to find the best features for classification. Moreover, artificial neural networks such as Multilayer Preceptron (MLP) neural network, Probabilistic Neural Network (PNN) and Generalized Regression Neural Network (GRNN) are applied to classify breast cancer into two groups; benign and malignant lesions. Training and recalling neural networks are obtained with considering four-fold cross validation.

Published in:

Biomedical Engineering (ICBME), 2010 17th Iranian Conference of

Date of Conference:

3-4 Nov. 2010