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Deep learning has been extensively applied to segmentation in medical imaging. U-Net proposed in 2015 shows the advantages of accurate segmentation of small targets and its scalable network architecture. With the increasing requirements for the performance of segmentation in medical imaging in recent years, U-Net has been cited academically more than 2500 times. Many scholars have been constantly developing the U-Net architecture. This paper summarizes the medical image segmentationdoi:10.1155/2022/4189781 pmid:35463660 pmcid:PMC9033381 fatcat:juxw7yh2j5f5le3kjl4tkacxju