生物医学工程研究2025，Vol.44Issue(6)：371-378,8.DOI:10.19529/j.cnki.1672-6278.2025.06.04
基于多尺度特征融合和滑动窗口注意力的胰腺分割网络
Pancreas segmentation network based on multi-scale feature fusion and sliding window attention
摘要
Abstract
To address the problem of blurred boundaries and low segmentation accuracy in pancreas segmentation,we proposed a pancreatic segmentation network MSW-HRNet.Firstly,by integrating depthwise separable convolution and spatial attention mecha-nisms,a multi-scale upsample block(MUB)was designed to restore the detailed information during the multi-scale upsampling process,enhance the segmentation ability for small-sized target regions.Then,the sliding-window attention block(Swin-Block)was fused to sense the global context information across scales,improve the discrimination ability of the model on lesion tissue and complex background,and enhance the performance of pancreatic boundary segmentation under complex structures.Experimental results demon-strated that the Dice coefficient of this method reached 82.11%on the NIH public dataset and 86.93%on the private pancreatitis data-set,outperforming mainstream segmentation models,confirming its superiority and practicality in handling complex pathological mor-phologies.关键词
胰腺分割/注意力机制/深度可分离卷积/HRNetKey words
Pancreatic segmentation/Attention mechanism/Depthwise separable convolution/HRNet分类
医药卫生引用本文复制引用
刘翼奇,辛国江,易晓雷,李旭辉,梁昊,吴荧洁..基于多尺度特征融合和滑动窗口注意力的胰腺分割网络[J].生物医学工程研究,2025,44(6):371-378,8.基金项目
湖南省教改课题项目(HNJG-2021-0584) （HNJG-2021-0584）
湖南省一流本科课程项目(2021-896). （2021-896）
