%0 Thesis %1 11 %A de Albuquerque Campos, Lúcio Flávio %D 2006 %K Mammogram aided analysis breast cancer component computer diagnosis independent networks neural %T Classificacão de Lesões em Mamografias Digitais usando Análise de Componentes Independentes e Redes Neurais Perceptron Multicamadas %X We propose a method for discrimination and classi¯cation of mammograms with benign, malignant and normal tissues using independent component analysis and neural networks. The method was tested for a mammogram set from MIAS database, and multilayer perceptron. The method obtained a success rate of 97.83% , with 97.5% of speci¯city and 98% of sensitivity.

@mastersthesis{11, abstract = {We propose a method for discrimination and classi¯cation of mammograms with benign, malignant and normal tissues using independent component analysis and neural networks. The method was tested for a mammogram set from MIAS database, and multilayer perceptron. The method obtained a success rate of 97.83% , with 97.5% of speci¯city and 98% of sensitivity.}, added-at = {2008-05-16T20:33:19.000+0200}, author = {de Albuquerque Campos, L{\'u}cio Fl{\'a}vio}, biburl = {https://www.bibsonomy.org/bibtex/2a5a0845d43c3e4498b66a0eb5d697024/roos}, interhash = {33edcbf5e8d02c0d2b386559b09abf62}, intrahash = {a5a0845d43c3e4498b66a0eb5d697024}, keywords = {Mammogram aided analysis breast cancer component computer diagnosis independent networks neural}, month = {March}, timestamp = {2008-05-16T20:33:19.000+0200}, title = {Classifica\c{c}\~{a}o de Les\~{o}es em Mamografias Digitais usando An{\'a}lise de Componentes Independentes e Redes Neurais Perceptron Multicamadas}, year = 2006 }