  In this work we present a method for lung nodules segmentation, their texture
classification and subsequent follow-up recommendation from the CT image of
lung. Our method consists of neural network model based on popular U-Net
architecture family but modified for the joint nodule segmentation and its
texture classification tasks and an ensemble-based model for the follow-up
recommendation. This solution was evaluated within the LNDb medical imaging
challenge and produced the best nodule segmentation result on the final
leaderboard.
