A Graph-Theoretical Clustering Method for Detecting Clusters of Micro-Calcifications in Mammographic Images

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	Similar Articles Articles by L. P. Cordella Articles by G. Percannella Articles by C. Sansone Articles by M. Vento

18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)

Dublin, Ireland

June 23-June 24

ISBN: 0-7695-2355-2

	ASCII Text	x
	L. P. Cordella, G. Percannella, C. Sansone, M. Vento, "A Graph-Theoretical Clustering Method for Detecting Clusters of Micro-Calcifications in Mammographic Images," Computer-Based Medical Systems, IEEE Symposium on, pp. 15-20, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05), 2005.

	BibTex	x
	@article{ 10.1109/CBMS.2005.8, author = {L. P. Cordella and G. Percannella and C. Sansone and M. Vento}, title = {A Graph-Theoretical Clustering Method for Detecting Clusters of Micro-Calcifications in Mammographic Images}, journal ={Computer-Based Medical Systems, IEEE Symposium on}, volume = {0}, year = {2005}, issn = {1063-7125}, pages = {15-20}, doi = {http://doi.ieeecomputersociety.org/10.1109/CBMS.2005.8}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer-Based Medical Systems, IEEE Symposium on TI - A Graph-Theoretical Clustering Method for Detecting Clusters of Micro-Calcifications in Mammographic Images SN - 1063-7125 SP15 EP20 A1 - L. P. Cordella, A1 - G. Percannella, A1 - C. Sansone, A1 - M. Vento, PY - 2005 KW - null VL - 0 JA - Computer-Based Medical Systems, IEEE Symposium on ER -

L. P. Cordella, Universit? degli Studi di Napoli "Federico II"

G. Percannella, Universit? degli Studi di Salerno

C. Sansone, Universit? degli Studi di Napoli "Federico II"

M. Vento, Universit? degli Studi di Salerno

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CBMS.2005.8

In this paper we propose a method based on a graph-theoretical cluster analysis for automatically finding cluster of micro-calcifications in mammographic images. It is applied to the image after a micro-calcification detection phase and is able to cope with the unavoidable false positives that each automatic detection algorithm produces.

The proposed approach has been tested on a standard database of 40 mammographic images and revealed to be very effective even when the detection phase gives rise to several false positives.

Citation:

L. P. Cordella, G. Percannella, C. Sansone, M. Vento, "A Graph-Theoretical Clustering Method for Detecting Clusters of Micro-Calcifications in Mammographic Images," cbms, pp.15-20, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05), 2005

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