ADGAN: Attribute-Driven Generative Adversarial Network for Synthesis and Multiclass Classification of Pulmonary Nodules.

Lung cancer is the leading cause of cancer-related deaths worldwide. According to the American Cancer Society, early diagnosis of pulmonary nodules in computed tomography (CT) scans can improve the five-year survival rate up to 70% with proper treatment planning. In this article, we propose an attribute-driven Generative Adversarial Network (ADGAN) for synthesis and multiclass classification of Pulmonary Nodules.

MDL-IWS: Multi-view Deep Learning with Iterative Watershed for Pulmonary Fissure Segmentation.

Pulmonary fissure segmentation is important for localization of lung lesions which include nodules at respective lobar territories. This can be very useful for diagnosis as well as treatment planning. In this paper, we propose a novel coarse-to-fine fissure segmentation approach by proposing a Multi-View Deep Learning driven Iterative WaterShed Algorithm (MDL-IWS).