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KMID : 1137820060270050291
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의공학회지
2006 Volume.27 No. 5 p.291 ~ p.299
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A Hierarchical Microcalcification Detection Algorithm Using SVM in Korean Digital Mammography
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Kwon Ju-Won
Kang Ho-Kyung
Ro Yong-Man
Kim Sung-Min
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Abstract
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A Computer-Aided Diagnosis system has been examined to reduce the effort of radiologist. In this paper, we propose the algorithm using Support Vector Machine(SVM) classifier to discriminate whether microcalcifications are malignant or benign tumors. The proposed method to detect microcalcifications is composed of two detection steps each of which uses SVM classifier. The coarse detection step finds out pixels considered high contrasts comparing with neighboring pixels. Then, Region of Interest(ROI) is generated based on microcalcification characteristics. The fine detection step determines whether the found ROIs are microcalcifications or not by merging potential regions using obtained ROIs and SVM classifier. The proposed method is specified on Korean mammogram database. The experimental result of the proposed algorithm presents robustness in detecting microcalcifications than the previous method using Artificial Neural Network as classifier even when using small training data.
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KEYWORD
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CAD, support vector machine(SVM), mammography
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