한국형 디지털 마모그래피에서 SVM을 이용한 계층적 미세석회화 검출 방법
A Hierarchical Microcalcification Detection Algorithm Using SVM in Korean Digital Mammography
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Abstract
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.
참고문헌 (14)
- "Long-term prediction of female breast cancer mortality in Korea", 6(1), pp.16~21 (2005)
- "X-ray characterization of normal and neoplastic breast tissues", 32(6), pp.675~695 (1987)
- "Full-Field Digital Mammography", 17(7), pp.1~22 (2002)
- "Computer Aided Diagnosis in Digital Mammograms Detection of Microcalcifications by Meta Heuristic Algorithms", 5(7), pp.41~55 (2005)
- "A report by the superintendent of insurance in consultation with the commissioner of health to the Governor and the legislature on the advisability of the adoption of a law that would expand the definition of mammography screening to include the review of X-Ray examinations by use of a computer aided detection device" (2003)
- "An SVM classifier to separate false signals from microcalcifications in digital mammograms", 46(6), pp.1651~1663 (2001)
- "A Microcalcification Detection Using Adaptive Contrast Enhancement on Wavelet Transform and Neural Network", e89-d(3), pp.1280~1287 (2005)
- "Differentiation of Benign and Malignant Breast Masses Comparison of Ultrasonography with Power Doppler Imaging and 99mTc-Scintimammography Journal of the Korean Radiological Society", 45(2), pp.215~220 (2001)
- "Neural Networks" (1999), New Jersey
- "A tutorial on support vector machines for pattern recognition", 2(2), pp.121~167 (1998)
- "A support vector machine approach for detection of microcalcifications", 21(12), pp.1552~1563 (2000)
- "A study on several Machine-learning methods for classification of Malignant and benign clustered microcalcifications", 24(3), pp.371~380 (2005)
- "Digital image processing" (2002), New Jersey
- "Introduction to MPEG-7 Multimedia Content Description Interface, John Wiley & Sons" (2002), LTD