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对称归一化配准的多图谱大脑扩散张量图像分割
引用本文:蔡文琴,王远军.对称归一化配准的多图谱大脑扩散张量图像分割[J].上海理工大学学报,2022,44(2):177-184.
作者姓名:蔡文琴  王远军
作者单位:上海理工大学 健康科学与工程学院, 上海 200093
基金项目:上海市自然科学基金资助项目(18ZR1426900)
摘    要:基于磁共振T1成像的全脑区分割方法及其在临床上的应用已经有较为广泛的研究,磁共振扩散张量成像凭借其在脑白质神经纤维束成像上的优势,近年来围绕扩散张量成像的理论和应用研究发展很快,针对扩散张量成像的脑区分割研究就成为一个必须要解决的问题.图像配准是精确实现脑区分割的重要技术步骤,传统的配准方法未考虑到图像的形变大小对配准...

关 键 词:扩散张量成像  多图谱分割  全脑区  对称图像归一化配准
收稿时间:2021/6/11 0:00:00

Segmentation of brain diffusion tensor images on multi-atlas for symmetric normalized registration
CAI Wenqin,WANG Yuanjun.Segmentation of brain diffusion tensor images on multi-atlas for symmetric normalized registration[J].Journal of University of Shanghai For Science and Technology,2022,44(2):177-184.
Authors:CAI Wenqin  WANG Yuanjun
Institution:School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Abstract:The whole brain segmentation method based on magnetic resonance T1 imaging and its clinical application have been extensively studied. With its advantages in imaging of white matter nerve fiber tracts, the theory and application of diffusion sensor imaging (DTI) has developed rapidly in recent years, and the study of brain segmentation for diffusion tensor imaging has become a problem that must be solved. Image registration is an important technical step to accurately realize brain segmentation. Traditional registration methods do not take into account the influence of image distortion on registration accuracy. The latest symmetric registration strategy is the best choice to solve this problem. Therefore, considering the characteristics of low resolution of diffusion tensor images and the technological advancement of symmetric registration, an automatic method to partition the whole brain of diffusion tensor images was proposed, and statistical SPSS software was used to compare AD patients and NC control group, and the accuracy of the proposed brain segmentation method was verified.
Keywords:diffusion tensor imaging  multi-atlas segmentation  whole brain regions  normalized registration of symmetric images
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