Detection and Segmentation of Masses in Mammograms by The Rule Based Elimination Approach

被引:0
|
作者
Ture, Hayati [1 ]
Kayikcioglu, Temel [1 ]
机构
[1] Karadeniz Tech Univ, Elekt & Elekt Muhendisligi Bolumu, Trabzon, Turkey
来源
2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2017年
关键词
Mammogram; mass; salient dense region; lifetime; rule-based-elimination;
D O I
暂无
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
In this study, a method was proposed that eliminated the non-suspicious salient regions for the detection and segmentation of masses in mammograms. Since suspicious regions are generally salient dense regions, the method firstly extracts the maximum regions of interest (ROIs) that have the optimum lifetime. Subsequently, these ROIs are segmented with the rule based elimination using morphological and intensity properties. The texture features taken from the suspicious regions are classified by Rus Boost method for detection of masses. The developed method has been tested on all mammograms, which includes mass, taken from the MIAS database. Experimental results demonstrate that the method achieves a satisfactory performance during the detection and segmentation of suspicious regions.
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页数:4
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