dc.contributor | Universidade Estadual Paulista (Unesp) | |
dc.contributor | Universidade de São Paulo (USP) | |
dc.contributor | Shu-Te University | |
dc.date.accessioned | 2014-05-27T11:23:42Z | |
dc.date.available | 2014-05-27T11:23:42Z | |
dc.date.created | 2014-05-27T11:23:42Z | |
dc.date.issued | 2008-11-24 | |
dc.identifier | Proceedings of the International Joint Conference on Neural Networks, p. 3181-3186, 2008. | |
dc.identifier | http://hdl.handle.net/11449/70639 | |
dc.identifier | 10.1109/IJCNN.2008.4634248 | |
dc.identifier | WOS:000263827202008 | |
dc.identifier | 2-s2.0-56349133254 | |
dc.identifier | 2098623262892719 | |
dc.identifier | 6542086226808067 | |
dc.identifier | 0000-0003-1086-3312 | |
dc.identifier | 0000-0002-0924-8024 | |
dc.description.abstract | This paper presents a method to enhance microcalcifications and classify their borders by applying the wavelet transform. Decomposing an image and removing its low frequency sub-band the microcalcifications are enhanced. Analyzing the effects of perturbations on high frequency subband it's possible to classify its borders as smooth, rugged or undefined. Results show a false positive reduction of 69.27% using a region growing algorithm. © 2008 IEEE. | |
dc.language | eng | |
dc.relation | Proceedings of the International Joint Conference on Neural Networks | |
dc.rights | Acesso aberto | |
dc.source | Scopus | |
dc.subject | Wavelet transforms | |
dc.subject | False positives | |
dc.subject | High frequencies | |
dc.subject | Low frequencies | |
dc.subject | Microcalcification | |
dc.subject | Microcalcifications | |
dc.subject | Region growing algorithms | |
dc.subject | Sub bands | |
dc.subject | Neural networks | |
dc.title | Microcalcification enhancement and classification on mammograms using the wavelet transform | |
dc.type | Actas de congresos | |