A deep 3D residual CNN for false-positive reduction in pulmonary nodule detection.

Purpose: The automatic detection of pulmonary nodules using CT scans improves the efficiency of lung cancer diagnosis, and false-positive reduction plays a significant role in the detection. In this paper, we focus on the false-positive reduction task and propose an effective method for this task.

Methods: We construct a deep 3D residual CNN (convolution neural network) to reduce false-positive nodules from candidate nodules.