Using Deep Learning for Classification of Early Lung Nodules on Computed Tomography Images

Abstract

Lung cancer is the leading cause of cancer mortality, accounting for approximately 20% of all cancer-related deaths. Nevertheless, despite the development of new therapeutic agents and technologies, only 16% of lung cancer patients are diagnosed at early stages. Therefore, to diagnose in early stages, when the nodules are very small, is a complex task for specialists and presents some challenges. To assist the specialists, the main purpose of this work is to propose the use of Deep Learning to classify 25,200 small pulmonary nodules balanced with diameter 5-10mm. The result was of 0.992 (+/-0.001) of area under ROC curve using 10-fold cross validation. The proposed method showed to be promising to assist the specialists in classification of small lung nodules.