Radiological data are massively produced in hospitals and are currently underexploited due to the limitation of radiologists to exhaustively and quantitatively analyze them. Deep convolutional neural networks showed tremendous performance in the analysis and recognition of objects in natural images, but the existing frameworks are not well adapted to medical image analysis. In this project, the student will design a lung nodule classification pipeline based on deep learning to automatically classify them as benign versus malignant, and compare it with existing approaches.