电子学报2025，Vol.53Issue(4)：1221-1231,11.DOI:10.12263/DZXB.20241058
基于小波域的复数卷积和复数Transformer的轻量级MR图像重建方法
Lightweight MR Image Reconstruction Network Based on Wavelet Domain Complex Convolution and Complex Transformer
摘要
Abstract
Convolutional neural networks(CNNs)have demonstrated remarkable capabilities in learning image priors from large-scale datasets,achieving exceptional performance across various image processing tasks.However,the local re-ceptive field inherently limit their ability to capture long-range dependencies between pixels.In contrast,the transformer ar-chitecture,renowned for its global receptive field,has exhibited outstanding performance in natural language processing and high-level vision tasks.Nevertheless,its computational complexity,which scales quadratically with image size,poses significant challenges for high-resolution image processing applications.Furthermore,many magnetic resonance(MR)re-construction algorithms exhibit limitations by either relying exclusively on magnitude data or processing real and imaginary components as separate channels,thereby failing to account for the intrinsic correlations within complex-valued images.By integrating complex convolution and complex transformer,an innovative hybrid module is introduced,which leverages the high-resolution spatial information extracted by CNNs to enhance the details of MR images and capture long-range features through global contextual information obtained by the self-attention module.Building on this hybrid module and wavelet transform,a lightweight MR image reconstruction method using complex convolution and complex transformer in the wave-let domain is further proposed.Experimental results on the Calgary-Campinas and fastMRI datasets demonstrate that the proposed model achieves superior reconstruction performance and while maintaining lower resource consumption compared to four representative MR image reconstruction algorithms.The source code is available at https://github.com/zhangxh-qhd/WCCTNet.关键词
MR图像重建/小波变换/轻量级网络/复数卷积/复数Transformer/感受野Key words
MR image reconstruction/wavelet transform/lightweight network/complex convolution/complex trans-former/receptive field分类
信息技术与安全科学引用本文复制引用
张晓华,练秋生..基于小波域的复数卷积和复数Transformer的轻量级MR图像重建方法[J].电子学报,2025,53(4):1221-1231,11.基金项目
河北省自然科学基金(No.F2022203030) Natural Science Foundation of Hebei Province(No.F2022203030) （No.F2022203030）
