生物医学工程研究2025，Vol.44Issue(3)：150-161,12.DOI:10.19529/j.cnki.1672-6278.2025.03.03
基于掩码建模技术的3D多模态脑影像重建算法研究
3D multimodal brain image reconstruction algorithm based masked modeling technology
摘要
Abstract
To address the issue that spatial information in 3D brain image data is complex and difficult to extract effective features,we proposed a 3D multimodal brain image reconstruction algorithm 3MbiRMA based on masked image modeling technology.A dual-branch structure was adopted to extract features of diffusion tensor imaging(DTI)and magnetic resonance imaging(MRI)3D brain image,to fuse multimodal features through feature decoupling,and to realize image reconstruction based on the decoder.Furthermore,the masking strategy and squeeze-space attention mechanism could not only significantly reduce information redundancy and enhance feature effectiveness,but also effectively reduce the computational complexity.Experimental results on the BeijingEN and ADNI data-sets indicated that the computational complexity of the 3MbiRMA was only 1/4 of that of the classical masked autoencoder(MAE)mod-el.Compared with the classical 3D reconstruction algorithms(3D UNet,VNet),the computational complexity of the 3MbiRMA was al-so significantly reduced.The algorithm can significantly improve the reconstruction performance and provide technical support for the re-search of brain image reconstruction.关键词
图像重建/多模态/掩码图像建模/特征提取/3D脑影像Key words
Image reconstruction/Multimodal/Mask image modeling/Feature extraction/3D brain imaging分类
医药卫生引用本文复制引用
贾浩靓,李翔,徐云峰,魏本征..基于掩码建模技术的3D多模态脑影像重建算法研究[J].生物医学工程研究,2025,44(3):150-161,12.基金项目
国家自然科学基金项目(62372280,62402297) （62372280,62402297）
山东省自然科学基金项目(2024MF139,2023QF094) （2024MF139,2023QF094）
青岛市科技惠民示范专项(23-2-8-smjk-2-nsh) （23-2-8-smjk-2-nsh）
齐鲁健康与卫生领军人才计划项目 （）
山东省青年科技人才托举工程 （）
山东中医药大学科学研究基金重点项目. （）
