An Expert Support System for Breast Cancer Diagnosis using Color Wavelet Features

Authors:
S. Issac Niwas;P. Palanisamy;Rajni Chibbar;W. J. Zhang
Affiliations:
Department of Electronics and Communication Engineering, National Institute of Technology (NIT), Tiruchirappalli, India 620015;Department of Electronics and Communication Engineering, National Institute of Technology (NIT), Tiruchirappalli, India 620015;Department of Pathology, University of Saskatchewan, Saskatoon, Canada S7N 5A9;Division of Biomedical Engineering and Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, Canada S7N 5A9
Venue:
Journal of Medical Systems
Year:
2012

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Abstract

Breast cancer diagnosis can be done through the pathologic assessments of breast tissue samples such as core needle biopsy technique. The result of analysis on this sample by pathologist is crucial for breast cancer patient. In this paper, nucleus of tissue samples are investigated after decomposition by means of the Log-Gabor wavelet on HSV color domain and an algorithm is developed to compute the color wavelet features. These features are used for breast cancer diagnosis using Support Vector Machine (SVM) classifier algorithm. The ability of properly trained SVM is to correctly classify patterns and make them particularly suitable for use in an expert system that aids in the diagnosis of cancer tissue samples. The results are compared with other multivariate classifiers such as Naïves Bayes classifier and Artificial Neural Network. The overall accuracy of the proposed method using SVM classifier will be further useful for automation in cancer diagnosis.