%0 Journal Article
%T High-Dimensional Spatial Standardization Algorithm for Diffusion Tensor Image Registration<br>High-Dimensional Spatial Standardization Algorithm for Diffusion Tensor Image Registration
%A Tao Guo
%A Quan Wang
%A Yi Wang
%A Kun Xie
%J 北京理工大学学报（自然科学中文版)
%D 2018
%R 10.15918/j.jbit1004-0579.18033
%X Three high dimensional spatial standardization algorithms are used for diffusion tensor image (DTI) registration, and seven kinds of methods are used to evaluate their performances. Firstly, the template used in this paper was obtained by spatial transformation of 16 subjects by means of tensor-based standardization. Then, high dimensional standardization algorithms for diffusion tensor images, including fractional anisotropy (FA) based diffeomorphic registration algorithm, FA based elastic registration algorithm and tensor-based registration algorithm, were performed. Finally, 7 kinds of evaluation methods, including normalized standard deviation, dyadic coherence, diffusion cross-correlation, overlap of eigenvalue-eigenvector pairs, Euclidean distance of diffusion tensor, and Euclidean distance of the deviatoric tensor and deviatoric of tensors, were used to qualitatively compare and summarize the above standardization algorithms. Experimental results revealed that the high-dimensional tensor-based standardization algorithms perform well and can maintain the consistency of anatomical structures.<br>Three high dimensional spatial standardization algorithms are used for diffusion tensor image (DTI) registration, and seven kinds of methods are used to evaluate their performances. Firstly, the template used in this paper was obtained by spatial transformation of 16 subjects by means of tensor-based standardization. Then, high dimensional standardization algorithms for diffusion tensor images, including fractional anisotropy (FA) based diffeomorphic registration algorithm, FA based elastic registration algorithm and tensor-based registration algorithm, were performed. Finally, 7 kinds of evaluation methods, including normalized standard deviation, dyadic coherence, diffusion cross-correlation, overlap of eigenvalue-eigenvector pairs, Euclidean distance of diffusion tensor, and Euclidean distance of the deviatoric tensor and deviatoric of tensors, were used to qualitatively compare and summarize the above standardization algorithms. Experimental results revealed that the high-dimensional tensor-based standardization algorithms perform well and can maintain the consistency of anatomical structures.
%K diffusion tensor imaging high dimensional spatial standardization registration template evaluation&lt
%K br&gt
%K diffusion tensor imaging high dimensional spatial standardization registration template evaluation
%U http://journal.bit.edu.cn/yw/bjlgyw/ch/reader/view_abstract.aspx?file_no=20180415&flag=1