Detecção do Câncer de Mama em Imagens Infravermelhas Utilizando Características Radiômicas - Carvalho, Elisson C.; Coelho, Alessandra M.; Baffa, Matheus F. O. (Proceedings of the Regional School of Applied Computing for Health (ERCAS), 2021)
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.