北京生物医学工程2025，Vol.44Issue(1)：16-25,10.DOI:10.3969/j.issn.1002-3208.2005.01.003
基于交叉双流特征融合配准网络对阿尔茨海默病中大脑皮质及皮下核团的图像分析
Image analysis of cortical and subcortical nuclei in Alzheimer disease based on intersected dual stream feature fusion registration network
摘要
Abstract
Objective An attention-based multiscale feature fusion network with intersected dual stream was proposed,namely MAFF-Net,for diffeomorphic brain image registration,in order to achieve rapid extraction and analysis of Alzheimer disease-related brain structure labels.Methods The intersected dual stream network was used to infer the mutual mapping relationship between image pairs,then the multiscale feature information was fused by introducing the attention mechanism,finally diffeomorphic registration was introduced to enhance the continuity and global smoothness of the deformation field and improve the registration quality.Brain image registration experiments were conducted on self-collected,OASIS-AD,and OASIS-Health datasets.The performance of the MAFF-Net model was validated using metrics by Dice similarity coefficient(DSC),recall,average surface distance(ASD),and the Jacobian determinant.Further analysis was performed on the brain structure label extraction results from the OASIS dataset.Results The experimental results of brain image registration showed that the MAFF-Net algorithm had DSC values of 0.832,0.853,and 0.865 on the three test sets,negative Jacobian determinant voxel ratios of 0.027％,0.192％,and 0.089％,recall values of 0.924,0.909,and 0.920,ASD values of 0.447 mm,0.387 mm,and 0.345 mm,with all but recall being superior to the comparison algorithm.The results of brain structural label analysis on the OASIS dataset showed that the volume and surface area of the cerebral cortex,hippocampus,and amygdala were closely related to age and health status.Conclusions The MAFF-Net model proposed in this paper can obtain accurate registration performance and label extraction results of brain MR Images,and provide auxiliary reference value for the early diagnosis of AD through the analysis of morphological characteristics of AD related brain structures.关键词
MR脑图像/微分同胚配准/注意力机制/阿尔茨海默病/脑解剖结构Key words
MR brain image/diffeomorphic registration/attention mechanism/Alzheimer disease/brain anatomical structure分类
医药卫生引用本文复制引用
李振宇,李恩慧,张童禹,张唯唯..基于交叉双流特征融合配准网络对阿尔茨海默病中大脑皮质及皮下核团的图像分析[J].北京生物医学工程,2025,44(1):16-25,10.基金项目
中国医学科学院医学与健康科技创新工程项目(CIFMS 2021-I2M-1-025)资助 （CIFMS 2021-I2M-1-025）
