CT理论与应用研究2026，Vol.35Issue(1)：48-57,10.DOI:10.15953/j.ctta.2025.052
基于多注意力融合增强Restormer的低剂量CT图像重建
Enhanced Restormer for Low-dose CT Image Reconstruction Based on Multi-attention Fusion
摘要
Abstract
Computed tomography(CT)technology plays a crucial role in medical diagnosis.Reducing the radiation dose per projection angle while maintaining a constant number of projection angles is an effective approach to achieving low-dose CT.However,this reduction often introduces significant noise into the reconstructed CT images,adversely affecting subsequent image analysis and research.To address this issue,we propose the enhanced restormer for low-dose CT image reconstruction based on multi-attention fusion(ERestormer)for low-dose CT image denoising.The network integrates channel attention,receptive field attention,and multi-head transposed attention to enhance the model's ability to focus on critical information,thereby improving its feature learning capacity.Furthermore,a feature fusion mechanism is introduced to strengthen feature reuse between the encoder and decoder.Experimental results show that the proposed network achieves superior denoising performance and enhanced preservation of image detail when compared to five classical networks:DNCNN,RED-CNN,UNet,Uformer,and Restormer.关键词
计算机断层成像/低剂量CT/通道注意力/感受野注意力/特征融合Key words
computed tomography/low-dose CT/channel attention/receptive field attention/feature fusion分类
信息技术与安全科学引用本文复制引用
吴送稳,方晨韵,乔志伟..基于多注意力融合增强Restormer的低剂量CT图像重建[J].CT理论与应用研究,2026,35(1):48-57,10.基金项目
国家自然科学基金面上项目(模型与数据耦合驱动的快速四维EPRI肿瘤氧成像(62071281)) （模型与数据耦合驱动的快速四维EPRI肿瘤氧成像(62071281）
中央引导地方科技发展资金项目(新型TV和学习先验联合约束的快速四维EPRI成像方法(YDZJSX2021A003)). （新型TV和学习先验联合约束的快速四维EPRI成像方法(YDZJSX2021A003）
