Classification of malignancy of lung nodules in CT images using Convolutional Neural Network - da Silva, Giovanni; Silva, Aristófanes; de Paiva, Anselmo; Gattass, Marcelo (Anais do Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS); 2016: Anais do XVI Workshop de Informática Médica, 2016)
Lung cancer presents the highest mortality rate, besides being one of the smallest survival rates after diagnosis. Thereby, early detection is extremely important for the diagnosis and treatment. This paper proposes three different architectures of Convolutional Neural Network (CNN), which is a deep learning technique, for classification of malignancy of lung nodules without computing the morphology and texture features. The methodology was tested onto the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), with the best accuracy of 82.3%, sensitivity of 79.4% and specificity 83.8%.