Performance evaluation of clustering algorithms on microcalcifications as mammography findings

被引:0
|
作者
Ikonomakis, Emmanouil K. [1 ]
Spyrou, George M. [2 ]
Ligomenides, Panos A. [2 ]
Vrahatis, Michael N. [1 ]
机构
[1] Univ Patras, Dept Math, Computat Intelligence Lab CILab, GR-26110 Patras, Greece
[2] Acad Athens, Biomed Res Fdn, Biomed Informat Unit, Athens 11527, Greece
来源
2013 IEEE 13TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE) | 2013年
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D O I
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中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Breast cancer can be prevented with regular mammography screening. Yet, the incorporation of Computational Intelligence relies on training classifiers on a set of predefined Regions of Interest (ROIs). Data Clustering has been applied to address the problem of ROI detection, yet no extensive research has been carried out on which algorithm to utilize. This contribution focuses on microcalcification clustering as a Data Clustering application, giving insights concerning the performance of three main clustering algorithms.
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页数:4
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