Abordagem Deep Learning para Classificação de Lesões Mamárias

• Roberto Pereira UFMA
• Caio Matos UFMA
• João Diniz UFMA
• Geraldo Braz Junior UFMA
• João de Almeida UFMA
• Aristófanes Silva UFMA
• Anselmo de Paiva UFMA

DOI: https://doi.org/10.5753/sbcas.2016.9906

Abstract

Female breast cancer is a major cause of death in western countries. Several computer aid techniques have been developed seeking to help radiologists in task of detection and diagnosis of breast abnormalities. Recently, deep learning techniques have shown good results in the image classification issues. In this paper, we present a metodology to distinguish mass and normal tissue extracted from mammograms using deep convolutional neural networks.

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