Detecção do Câncer de Mama em Imagens Infravermelhas Utilizando Características Radiômicas

• Elisson C. Carvalho IF Sudeste MG
• Alessandra M. Coelho IF Sudeste MG
• Matheus F. O. Baffa USP

DOI: https://doi.org/10.5753/ercas.2021.17433

Abstract

Breast cancer is the second most common type of cancer around the world. When early diagnosed, the patient has a better prognosis and increases their chances of cure. This work proposes the development of an infrared image classification method to aid in the diagnosis of breast cancer. For this, radiomic-based features were used to represent the image along with a Deep Neural Network for pattern recognition and to build a classification model. We conducted an experiment following the Cross-Validation protocol and the proposed method reached an accuracy of 97.27% and a sensitivity of 96.33%. New medical imaging modalities have proven effective in the early detection of breast cancer.

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