电子科技2024，Vol.37Issue(1)：72-80,9.DOI:10.16180/j.cnki.issn1007-7820.2024.01.011
基于深度学习的医学图像分割方法研究进展
Research Progress of Medical Image Segmentation Method Based on Deep Learning
摘要
Abstract
Medical image processing technology has developed rapidly with the rise of deep learning.The medi-cal image segmentation technology based on deep learning has become the mainstream method in the segmentation field,which solves the shortcomings of the traditional segmentation method's insufficient segmentation accuracy.This technology has been maturely applied to the segmentation of some pathological images.This study introduces and compares the segmentation methods based on deep learning in recent years,and focuses on the major contributions of U-Net and its improved models in the segmentation field,and summarizes the common medical image modalities and evaluation indicators of segmentation algorithms and commonly used segmentation data sets.Finally,the future devel-opment of medical image segmentation technology is prospected.关键词
医学图像分割技术/深度学习/U-Net/分割算法/图像处理/医学图像模态/评价指标/分割数据集Key words
medical image segmentation technology/deep learning/U-Net/segmentation algorithm/image pro-cessing/medical image modality/evaluation index/segmentation data set分类
医药卫生引用本文复制引用
李增辉,王伟..基于深度学习的医学图像分割方法研究进展[J].电子科技,2024,37(1):72-80,9.基金项目
全军"双重"学科建设项目(2020SZ10) （2020SZ10）
军内科研项目(HJ20191A020141)PLA"Dual"Discipline Construction Project(2020SZ10) （HJ20191A020141）
Military Scientific Research Project(HJ20191A020141) （HJ20191A020141）
