*6.2.2 Image segmentation*

The task of image segmentation is to map an input image into a segmented output image. The encoder-decoder networks have been developed dramatically in recent years and achieve a significant impact on computer vision. Specifically, there are mainly two types of tasks including semantic segmentation and instance segmentation. In 2015, Long et al. [20] firstly showed that an end-to-end fully CNN can achieve state-of-art in image segmentation tasks. Similar work has also been introduced in [6] in 2015, in which a U-Net architecture is proposed for medical image segmentation, and the main advance in this architecture is that the shortcut connection method is also used between the encoder and decoder network. Since then, a series of papers based on these two methods have been published. In particular nowadays the U-Net based architectures are widely used for the medical image diagnosis.
