I. Introduction
With the help of deep learning, automatic medical image segmentation achieves promising results and liberates pathologists from time-consuming and tedious labeling. U-Net [1], a fully convolutional neural network architecture, is widely used for medical image segmentation. The increasing model complexity [2] –[5] for U-Net improvement and diverse deployment requirements raise the demands for U-Net compression.