4.6 Article

Advanced Fuzzy Sets and Genetic Algorithm Optimizer for Mammographic Image Enhancement

期刊

ELECTRONICS
卷 12, 期 15, 页码 -

出版社

MDPI
DOI: 10.3390/electronics12153269

关键词

advanced fuzzy sets; linguistic hedges; intuitionist fuzzy set; pythagorean fuzzy set; fermatean fuzzy set; genetic algorithm; contrast enhancement; mammography images; OWA operators; image fusion; multi-fuzzy set

向作者/读者索取更多资源

This paper discusses the development of Computer Aided Diagnosis (CADx) Systems for the classification of abnormalities in mammography. The uncertainties in the shape and geometry of the breast parenchyma can lead to inaccurate diagnoses. Fuzzy processing, using fuzzy sets, can handle imperfect data arising from vagueness and ambiguity. Fuzzy contrast enhancement improves edge detection and classification features.
A well-researched field is the development of Computer Aided Diagnosis (CADx) Systems for the benign-malignant classification of abnormalities detected by mammography. Due to the nature of the breast parenchyma, there are significant uncertainties about the shape and geometry of the abnormalities that may lead to an inaccurate diagnosis. These same uncertainties give mammograms a fuzzy character that is essential to the application of fuzzy processing. Fuzzy set theory considers uncertainty in the form of a membership function, and therefore fuzzy sets can process imperfect data if this imperfection originates from vagueness and ambiguity rather than randomness. Fuzzy contrast enhancement can improve edge detection and, by extension, the quality of related classification features. In this paper, classical (Linguistic hedges and fuzzy enhancement functions), advanced fuzzy sets (Intuitionistic fuzzy set (& UIota;FS), Pythagorean fuzzy set (PFS), and Fermatean fuzzy sets (FFS)), and a Genetic Algorithm optimizer are proposed to enhance the contrast of mammographic features. The advanced fuzzy sets provide better information on the uncertainty of the membership function. As a result, the intuitionistic method had the best overall performance, but most of the techniques could be used efficiently, depending on the problem that needed to be solved. Linguistic methods could provide a more manageable way of spreading the histogram, revealing more extreme values than the conventional methods. A fusion technique of the enhanced mammography images with Ordered Weighted Average operators (OWA) achieves a good-quality final image.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据