Microcalcification enhancement and classification on mammograms using the wavelet transform
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Data
2008-11-24
Autores
Docusse, Tiago A. [UNESP]
Furlani, Jullyene R. [UNESP]
Romano, Rodolfo P. [UNESP]
Guido, Rodrigo C.
Chen, Shi-Huang
Marranghello, Norian [UNESP]
Pereira, Aledir S. [UNESP]
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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.
Descrição
Palavras-chave
Wavelet transforms, False positives, High frequencies, Low frequencies, Microcalcification, Microcalcifications, Region growing algorithms, Sub bands, Neural networks
Como citar
Proceedings of the International Joint Conference on Neural Networks, p. 3181-3186, 2008.