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Multi-scaled morphological features for the characterization of mammographic masses using statistical classification schemes.
Artif Intell Med. 2007 Sep;41(1):39-55. doi: 10.1016/j.artmed.2007.06.004. Epub 2007 Aug 21.
Artif Intell Med. 2007.
PMID: 17714924
Mammographic masses characterization based on localized texture and dataset fractal analysis using linear, neural and support vector machine classifiers.
Mavroforakis ME, Georgiou HV, Dimitropoulos N, Cavouras D, Theodoridis S.
Mavroforakis ME, et al.
Artif Intell Med. 2006 Jun;37(2):145-62. doi: 10.1016/j.artmed.2006.03.002. Epub 2006 May 23.
Artif Intell Med. 2006.
PMID: 16716579
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A fully automated scheme for mammographic segmentation and classification based on breast density and asymmetry.
Tzikopoulos SD, Mavroforakis ME, Georgiou HV, Dimitropoulos N, Theodoridis S.
Tzikopoulos SD, et al. Among authors: mavroforakis me.
Comput Methods Programs Biomed. 2011 Apr;102(1):47-63. doi: 10.1016/j.cmpb.2010.11.016.
Comput Methods Programs Biomed. 2011.
PMID: 21306782
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Significance analysis of qualitative mammographic features, using linear classifiers, neural networks and support vector machines.
Mavroforakis M, Georgiou H, Dimitropoulos N, Cavouras D, Theodoridis S.
Mavroforakis M, et al.
Eur J Radiol. 2005 Apr;54(1):80-9. doi: 10.1016/j.ejrad.2004.12.015.
Eur J Radiol. 2005.
PMID: 15797296
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A geometric approach to support vector machine (SVM) classification.
Mavroforakis ME, Theodoridis S.
Mavroforakis ME, et al.
IEEE Trans Neural Netw. 2006 May;17(3):671-82. doi: 10.1109/TNN.2006.873281.
IEEE Trans Neural Netw. 2006.
PMID: 16722171
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A geometric nearest point algorithm for the efficient solution of the SVM classification task.
Mavroforakis ME, Sdralis M, Theodoridis S.
Mavroforakis ME, et al.
IEEE Trans Neural Netw. 2007 Sep;18(5):1545-9. doi: 10.1109/tnn.2007.900237.
IEEE Trans Neural Netw. 2007.
PMID: 18220205
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