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Conference Paper
A Review of Breast Tissue Classification in Mammograms
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- Authors
- Gen Sheng Zhang, Wei Wang, Ju Cheol Moon, Jeong K. Pack, Soon Ik Jeon
- Issue Date
- 2011-11
- Citation
- ACM Research in Applied Computation Symposium (RACS) 2011, pp.232-237
- Publisher
- ACM
- Language
- English
- Type
- Conference Paper
- Abstract
- For women in the U.S. breast cancer is the most commonly diagnosed cancer besides skin cancer and has become one of the major health issues in recent decades. Early detection through screening is one of key factors to reduce the death rates. The strong correlation between abnormality of breast tissues presented in mammograms and breast cancer shows that radiologists could benefit from Computer-Aided Diagnosis (CAD) systems with abilities of automated breast tissueclassification. This paper reviews recent advances in classification technologies of breast tissues. The major contribution of this paper is that we extensivelydiscuss recent breast tissue classification technologie sand compare three different types of approaches. According to our survey, we found that machine learning approaches could be chosen as anappropriate classification technology for a CAD system, considering efficiency and compatibility. © 2011 ACM.
- KSP Keywords
- Breast Cancer(BC), Computer-aided diagnosis (CAD) systems, Death rates, Early Detection, Key factor, Machine Learning Approach, Skin Cancer, breast tissue classification, health issues, strong correlation