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Conference Paper
A New Histogram-Based Breast Cancer Image Classifier Using Gaussian Mixture Model
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- Authors
- Zhe Li, Sung Shin, Soon I. Jeon, Seong H. Son, Jeong K. Pack
- Issue Date
- 2012-10
- Citation
- Research in Applied Computation Symposium (RACS) 2012, pp.143-147
- Language
- English
- Type
- Conference Paper
- Abstract
- 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 Keywords
- Breast cancer Detection, Breast tumor, Gaussian Mixture Models(GMM), Gaussian mixture(GM), Histogram-Based, Image Classification, Image classifier, new method