상세정보
학술대회
A New Histogram-Based Breast Cancer Image Classifier Using Gaussian Mixture Model
- 발행일
- 201210
- 출처
- Research in Applied Computation Symposium (RACS) 2012, pp.143-147
- 협약과제
- 12PR3800, 전자파 이용 조기진단 고정밀 MT 시스템 개발, 전순익
- 초록
- Early stage breast cancer detection is a critical challenge to improve survive rate, and thus it is extremely important to perform breast tumor image classification. In this paper, we propose a new method based on Gaussian Mixture Model (GMM) to classify one input breast tumor image into two different classes (benign class and malignant class). The main contribution of our proposed approach is to innovatively design the breast tumor image classifier using histogram-based GMM. This paper also represents extensive experimental results using this new method. The results show that this new histogram-GMM-based method is effective and accurate to classify breast tumor images into different classes. Copyright 2012 ACM.
- KSP 제안 키워드
- Breast Cancer(BC), Breast cancer detection, Gaussian mixture Model(GMM), Histogram-based, Image classification, Image classifier, breast tumor, new method