计算机科学与探索2024，Vol.18Issue(6)：1383-1403,21.DOI:10.3778/j.issn.1673-9418.2307069
U型卷积网络在乳腺医学图像分割中的研究综述
Review of U-Net-Based Convolutional Neural Networks for Breast Medical Image Segmentation
摘要
Abstract
U-Net and its variants have showcased exceptional performance in the domain of breast medical image segmentation.By employing a fully convolutional network(FCN)structure for semantic segmentation,the symmet-rical structure of U-Net offers remarkable flexibility and adaptability.It can be tailored to diverse image segmenta-tion tasks and challenges by adjusting network depth and incorporating new modules,leaving a significant impact on subsequent network designs.This paper aims to delve into the application of U-shaped convolutional networks in breast medical image segmentation,categorizing and summarizing U-shaped convolutional networks used for this purpose in recent years.It outlines the widely used breast medical image datasets and evaluation metrics,discusses common data augmentation techniques,and provides a detailed introduction to the network structure of the U-Net model along with traditional segmentation methods for breast medical images.Furthermore,it summarizes the im-provements made to the U-Net network structure for breast medical image segmentation,including modifications like residual structures,multi-scale features,dilation mechanisms,attention mechanisms,skip connection mecha-nisms,and integration with Transformers.Finally,it addresses the current challenges and problems encountered in breast medical image segmentation and offers insights into future research directions.关键词
医学图像分割/U型卷积网络/深度学习/乳腺疾病/图像处理Key words
medical image segmentation/U-shaped convolutional network/deep learning/breast disease/image processing分类
信息技术与安全科学引用本文复制引用
蒲秋梅,殷帅,李正茂,赵丽娜..U型卷积网络在乳腺医学图像分割中的研究综述[J].计算机科学与探索,2024,18(6):1383-1403,21.基金项目
国家自然科学基金(31971311).This work was supported by the National Natural Science Foundation of China(31971311). （31971311）
