基于U-Net变体的医学图像分割算法综述OA北大核心CSTPCD

The simple and efficient network structure of U-Net is widely used in medical image segmentation,and many scholars have made various researches on the U-Net structure.This paper elucidates in the following:firstly,the paper summarizes the key challenges of the U-Net network in the field of medical image segmentation;next,it elaborates the formats and characteristics of medical image datasets that are commonly used in the U-Net network;then,it summarizes the six improvement mechanism of U-Net:skip connection mechanism,generative adversarial network,residual connec-tion mechanism,3D-UNet,Transformer mechanism,and dense connecting mechanism.Finally,the paper discusses the rela-tionship between these improvement mechanisms and commonly used medical data formats,and points out the ideas and directions for future improvement,so as to stimulate the unlimited potential of U-Net in medical image segmentation.