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Accurate lung cancer diagnosis is crucial to select the best course of action for treating the patient. From a simple chest CT volume, it is necessary to identify whether the cancer has spread to nearby lymph nodes or not. It is equally important to know precisely where each malignant lymph node is with respect to the surrounding anatomical structures and the airways. In this paper, we introduce a new data-set containing annotations of fifteen different anatomical structures in the mediastinal area, including lymph nodes of varying sizes. We present a 2D pipeline for semantic segmentation and instance detection of anatomical structures and potentially malignant lymph nodes in the mediastinal area.

We propose a 2D pipeline combining the strengths of U-Net for pixel-wise segmentation using a loss function dealing with data imbalance and …