智能系统学报2025，Vol.20Issue(5)：1266-1280,15.DOI:10.11992/tis.202409011
基于空频协同的CNN-Transformer多器官分割网络
CNN-Transformer multiorgan segmentation network based on space-frequency collaboration
摘要
Abstract
Current mainstream medical multi-organ segmentation networks fail to fully exploit the local detail extrac-tion capabilities of convolutional neural network(CNN)and the global information capturing potential of Transformers.Additionally,they lack an effective mechanism for collaboration modeling of spatial and frequency domain features.To address these limitations,we propose a dual-branch encoder-decoder network based on CNN-Transformer with space-frequency collaboration.The network incorporates space-frequency collaborative attention in local branches,allowing the network to capture richer local details from both the frequency and spatial domains.A multi-view frequency domain extractor is designed in the global branch.This module improves the model's ability to jointly model spatial and fre-quency features and its generalization performance through joint modeling of spectral layers and self-attention layers.In addition,a local and global feature fusion module is designed to effectively integrate the local detail information of the CNN branch and the global information of the Transformer branch,solving the problem that the network cannot balance local details and global receptive fields.Experimental results demonstrate that this architecture effectively addresses the challenges posed by blurred boundary segmentation in medical images,which often leads to mis-segmentation of or-gans,significantly enhancing the accuracy of multi-organ segmentation while simultaneously reducing the computation-al costs and the number of parameters required.关键词
多器官分割/空频协同/多视图频域/注意力机制/CNN/Transformer/协同注意力/局部-全局特征融合Key words
multiorgan segmentation/space-frequency collaboration/multiview frequency domain/attention mechan-ism/CNN/Transformer/coattention/local-global feature fusion分类
信息技术与安全科学引用本文复制引用
王梦溪,雷涛,姜由涛,刘乐,刘少庆,王营博..基于空频协同的CNN-Transformer多器官分割网络[J].智能系统学报,2025,20(5):1266-1280,15.基金项目
国家自然科学基金项目(62271296,62201334) （62271296,62201334）
陕西省创新能力支撑计划项目(2025RS-CXTD-012) （2025RS-CXTD-012）
陕西高校青年创新团队项目(23JP014,23JP022). （23JP014,23JP022）
