Classification for Breast MRI Using Support Vector Machine

Authors:
Chuin-Mu Wang;Xiao-Xing Mai;Geng-Cheng Lin;Chio-Tan Kuo
Affiliations:
-;-;-;-
Venue:
CITWORKSHOPS '08 Proceedings of the 2008 IEEE 8th International Conference on Computer and Information Technology Workshops
Year:
2008

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Abstract

Magnetic Resonance Image (MRI) was harmless to the human body and used on the clinical trial extensively in recent years. In this study, we want to detect the tissues of breast form the multi-spectral MR image. Because multi-spectral MR image are scanning the same slice with various frequencies and parameters and it can obtain intact information. In the image classification, we apply support vector machine (SVM) on breast multi-spectral magnetic resonance image to classify the tissues of breast separately. The classification results would assist doctor to judge and sift the breast tumor. In order to further evaluate its performance, the C-means (CM) classification method is compared with SVM. By some experiments, the result of SVM is better than C-mean.