Automatic detection of microcalcification clusters using fuzzy logic and wavelet transformation

被引：0

作者：

Cheng, HD ^{[1
]}

Liu, XY ^{[1
]}

Shi, XJ ^{[1
]}

Hu, LM ^{[1
]}

机构：

[1] Utah State Univ, Dept Comp Sci, Logan, UT 84322 USA

来源：

Proceedings of the 8th Joint Conference on Information Sciences, Vols 1-3 | 2005年

关键词：

fuzzy logic; wavelet transformation; maximum entropy principle; microcalcification;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In 2004, 215,990 new cases of breast cancer are expected to occur among women in the United States. Early detection of breast cancer is essential in breast cancer control. In this paper, a novel approach to microcalcification detection, based on fuzzy logic and wavelet transformation is presented. Then, the free-response operating characteristic curve (FROC) is used to evaluate the performance. Compared with existing algorithms using the same set of mammograms, the proposed algorithm achieves better results, producing both low FPs and low FNs rates.

引用

页码：686 / 689

页数：4

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