Open Science Research Excellence
%0 Journal Article
%A Sepehr M.H.Jamarani and  M.H.Moradi and  H.Behnam and  G.A.Rezai Rad
%D 2007 
%J  International Journal of Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 12, 2007
%T Intelligent System for Breast Cancer Prognosis using Multiwavelet Packets and Neural Network
%U http://waset.org/publications/13482
%V 12
%X This paper presents an approach for early breast
cancer diagnostic by employing combination of artificial neural
networks (ANN) and multiwaveletpacket based subband image
decomposition. The microcalcifications correspond to high-frequency
components of the image spectrum, detection of microcalcifications
is achieved by decomposing the mammograms into different
frequency subbands,, reconstructing the mammograms from the
subbands containing only high frequencies. For this approach we
employed different types of multiwaveletpacket. We used the result
as an input of neural network for classification. The proposed
methodology is tested using the Nijmegen and the Mammographic
Image Analysis Society (MIAS) mammographic databases and
images collected from local hospitals. Results are presented as the
receiver operating characteristic (ROC) performance and are
quantified by the area under the ROC curve.
%P 630 - 635