TY - GEN
T1 - Breast abnormality detection incorporating breast density information based on independent components analysis
AU - Petroudi, Styliani
AU - Nicolaou, Nicoletta
AU - Georgiou, Julius
AU - Brady, Michael
PY - 2008/9/9
Y1 - 2008/9/9
N2 - This paper introduces an approach to breast abnormality classification which incorporates breast density information. Features are extracted by a novel technique based on Independent Component Analysis, which decomposes the selected images into sets of independent source regions and corresponding basis functions (weights). The coefficients which result from the source regions are used in turn to describe normality and abnormality. The method has been tested on the MIAS database and has high sensitivity.
AB - This paper introduces an approach to breast abnormality classification which incorporates breast density information. Features are extracted by a novel technique based on Independent Component Analysis, which decomposes the selected images into sets of independent source regions and corresponding basis functions (weights). The coefficients which result from the source regions are used in turn to describe normality and abnormality. The method has been tested on the MIAS database and has high sensitivity.
UR - http://www.scopus.com/inward/record.url?scp=50949132002&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-70538-3_92
DO - 10.1007/978-3-540-70538-3_92
M3 - Conference contribution
AN - SCOPUS:50949132002
SN - 3540705376
SN - 9783540705376
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 667
EP - 673
BT - Digital Mammography - 9th International Workshop, IWDM 2008, Proceedings
T2 - 9th International Workshop on Digital Mammography, IWDM 2008
Y2 - 20 July 2008 through 23 July 2008
ER -