Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
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A Hierarchical Microcalcification Detection Algorithm Using SVM in Korean Digital Mammography

한국형 디지털 마모그래피에서 SVM을 이용한 계층적 미세석회화 검출 방법

  • Kwon, Ju-Won (Image and Video Systems Lab., Information and Communications University) ;
  • Kang, Ho-Kyung (Image and Video Systems Lab., Information and Communications University) ;
  • Ro, Yong-Man (Image and Video Systems Lab., Information and Communications University) ;
  • Kim, Sung-Min (Department of Biomedical Engineering, School of Medicine, Konkuk University)
  • 권주원 (한국정보통신대학교 멀티미디어그룹 영상 및 비디오 시스템 연구실) ;
  • 강호경 (한국정보통신대학교 멀티미디어그룹 영상 및 비디오 시스템 연구실) ;
  • 노용만 (한국정보통신대학교 멀티미디어그룹 영상 및 비디오 시스템 연구실) ;
  • 김성민 (건국대학교 의공학과)
  • Published : 2006.10.31
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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.

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References

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