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