DocumentCode :
667212
Title :
Performance evaluation of clustering algorithms on microcalcifications as mammography findings
Author :
Ikonomakis, Emmanouil K. ; Spyrou, George M. ; Ligomenides, Panos A. ; Vrahatis, M.N.
Author_Institution :
Dept. of Math., Univ. of Patras, Patras, Greece
fYear :
2013
fDate :
10-13 Nov. 2013
Firstpage :
1
Lastpage :
4
Abstract :
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.
Keywords :
cancer; image classification; mammography; medical image processing; object detection; pattern clustering; performance evaluation; ROI detection problem; breast cancer; classifiers training; computational intelligence; data clustering; digital mammography screening; mammography findings; microcalcification clustering algorithm; performance evaluation; regions-of-interest; Biomedical imaging; Breast; Clustering algorithms; Image segmentation; Noise; Optical wavelength conversion; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Bioengineering (BIBE), 2013 IEEE 13th International Conference on
Conference_Location :
Chania
Type :
conf
DOI :
10.1109/BIBE.2013.6701550
Filename :
6701550
Link To Document :
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