文章基本信息

标题：A Novel Breast mass segmentation method based on patch merging and GHFCM
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作者：Shenghua Gu ; Yunjie Chen ; Jin Wang 等
期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2015
卷号：8
期号：10
页码：427-436
DOI：10.14257/ijhit.2015.8.10.39
出版社：SERSC
摘要：Breast cancer is regarded as one of the most frequent mortality causes among women. It is very important to create a system to diagnose suspicious masses in mammograms for early breast cancer detection. In this paper, we propose an automatic breast mass segmentation method based on patch merging method and generalized hierarchical F uzzy C Means (GHFCM). The patch merging method is used to obtain the adaptive region of interest (ROI), while the GHFCM method which is able to overcome the drawbacks of effect of image noise and Euclidean distance FCM which is sensitive to outliers is used to obtain the precisely mass segmentation results. The new method is evaluated over MiniMIAS dataset. The segmentation performance from experimentations demonstrates that our method outperforms the other compared methods.
关键词：Breast mass segmentation; Hierarchical distance function; ; Generalized mean; Patch merging; GHFCM