计算机工程与应用2024，Vol.60Issue(11)：32-49,18.DOI:10.3778/j.issn.1002-8331.2310-0335
基于U-Net变体的医学图像分割算法综述
Review of Medical Image Segmentation Algorithms Based on U-Net Variants
摘要
Abstract
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.关键词
U-Net变体/医学图像分割/语义分割/深度学习/改进机制Key words
U-Net variants/medical image segmentation/semantic segmentation/deep learning/improved mechanism分类
信息技术与安全科学引用本文复制引用
崔珂,田启川,廉露..基于U-Net变体的医学图像分割算法综述[J].计算机工程与应用,2024,60(11):32-49,18.基金项目
北京建筑大学研究生教育教学质量提升项目(J2022012) （J2022012）
北京建筑大学教育教学研究项目(Y2130) （Y2130）
北京建筑大学混合式课程建设项目(YC23019). （YC23019）
