Docusse, Tiago A. [UNESP]Furlani, Jullyene R. [UNESP]Romano, Rodolfo P. [UNESP]Guido, Rodrigo C.Chen, Shi-HuangMarranghello, Norian [UNESP]Pereira, Aledir S. [UNESP]2014-05-272014-05-272008-11-24Proceedings of the International Joint Conference on Neural Networks, p. 3181-3186, 2008.http://hdl.handle.net/11449/70639This 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.3181-3186engWavelet transformsFalse positivesHigh frequenciesLow frequenciesMicrocalcificationMicrocalcificationsRegion growing algorithmsSub bandsNeural networksTrabalho apresentado em evento10.1109/IJCNN.2008.4634248WOS:000263827202008Acesso aberto2-s2.0-56349133254209862326289271965420862268080670000-0003-1086-33120000-0002-0924-8024