Custom 3D fMRI Registration Template Construction Method Based on Time-Series Fusion

被引:2
|
作者
Wang, Zhongyang [1 ,2 ]
Xin, Junchang [1 ,2 ]
Shen, Huixian [1 ]
Chen, Qi [3 ]
Wang, Zhiqiong [3 ]
Wang, Xinlei [1 ]
机构
[1] Northeastern Univ, Sch Comp Sci & Engn, Shenyang 110819, Peoples R China
[2] Northeastern Univ, Key Lab Big Data Management & Analyt, Shenyang 110819, Peoples R China
[3] Northeastern Univ, Coll Med & Biol Informat Engn, Shenyang 110819, Peoples R China
基金
中国国家自然科学基金;
关键词
fMRI template; fused slices; custom; sequences; IMAGE REGISTRATION; LEARNING FRAMEWORK;
D O I
10.3390/diagnostics12082013
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
As the brain standard template for medical image registration has only been constructed with an MRI template, there is no three-dimensional fMRI standard template for use, and when the subject's brain structure is quite different from the standard brain structure, the registration to the standard space will lead to large errors. Registration to an individual space can avoid this problem. However, in the current fMRI registration algorithm based on individual space, the reference image is often selected by researchers or randomly selected fMRI images at a certain time point. This makes the quality of the reference image very dependent on the experience and ability of the researchers and has great contingency. Whether the reference image is appropriate and reasonable affects the rationality and accuracy of the registration results to a great extent. Therefore, a method for constructing a 3D custom fMRI template is proposed. First, the data are preprocessed; second, by taking a group of two-dimensional slices corresponding to the same layer of the brain in three-dimensional fMRI images at multiple time points as image sequences, each group of slice sequences are registered and fused; and finally, a group of fused slices corresponding to different layers of the brain are obtained. In the process of registration, in order to make full use of the correlation information between the sequence data, the feature points of each two slices of adjacent time points in the sequence are matched, and then according to the transformation relationship between the adjacent images, they are recursively forwarded and mapped to the same space. Then, the fused slices are stacked in order to form a three-dimensional customized fMRI template with individual pertinence. Finally, in the classic registration algorithm, the difference in the registration accuracy between using a custom fMRI template and different standard spaces is compared, which proves that using a custom template can improve the registration effect to a certain extent.
引用
收藏
页数:18
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