Microcalcification enhancement and classification on mammograms using the wavelet transform
| Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
|---|---|
| Data(s) |
27/05/2014
27/05/2014
24/11/2008
|
| Resumo |
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. |
| Formato |
3181-3186 |
| Identificador |
http://dx.doi.org/10.1109/IJCNN.2008.4634248 Proceedings of the International Joint Conference on Neural Networks, p. 3181-3186, 2008. http://hdl.handle.net/11449/70639 10.1109/IJCNN.2008.4634248 WOS:000263827202008 2-s2.0-56349133254 |
| Idioma(s) |
eng |
| Relação |
Proceedings of the International Joint Conference on Neural Networks |
| Direitos |
closedAccess |
| Palavras-Chave | #Wavelet transforms #False positives #High frequencies #Low frequencies #Microcalcification #Microcalcifications #Region growing algorithms #Sub bands #Neural networks |
| Tipo |
info:eu-repo/semantics/conferencePaper |
