关键词: 肺结节, U-Net, 密集连接, 语义分割

Abstract:

In order to accurately segment lung nodules from CT images, an improved U-Net based method is proposed for lung nodule segmentation. The dense connection introduced into the network can not only strengthen the transmission and utilization of features, but also avoid the vanishing gradient problem. Meanwhile, an improved hybrid loss function is adopted to address class imbalance problem. The experimental results on the public LIDC-IDRI database show that the proposed method can achieve Dice similarity coefficient, precision and recall of 84.48%，85.35% and 83.81%, respectively. Compared with some segmentation methods, the proposed method can accurately segment lung nodules with good performance.

Key words: lung nodules, U-Net, dense connection, semantic segmentation