Brain function connection network analysis method based on resting state functional magnetic resonance image

A technology of functional magnetic resonance and brain functional connection, which is applied in the field of brain functional connection network construction, can solve the problems of great influence on brain network construction and analysis, and achieve the effect of improving the performance of the model

Pending Publication Date: 2022-03-29
FUZHOU UNIV
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The selection of brain templates in existing methods has a ...

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  • Brain function connection network analysis method based on resting state functional magnetic resonance image
  • Brain function connection network analysis method based on resting state functional magnetic resonance image
  • Brain function connection network analysis method based on resting state functional magnetic resonance image

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Embodiment Construction

[0050] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0051] Please refer to figure 1 , the present invention provides a method for analyzing brain functional connectivity networks based on resting-state functional magnetic resonance images, comprising the following steps:

[0052] Step S1: preprocessing the functional magnetic resonance images, in this embodiment, all rs-fMRI images are preprocessed by DPARSF. The preprocessing process includes. 1) Dropout of top 10 time points, 2) Slice time correction, 3) Head motion correction, 4) Regression of interfering covariates, 5) Bandpass filtering (0.01-0.1Hz), 6) Normalization to MNI152 Standard anatomical space, 7) smooth space (FWHM=4mm).

[0053]Step S2: Segment all rs-fMRI images using templates of three different scales, namely AAL, with 116 brain regions; Craddock 200 (CC200), with 200 brain regions; Brainnetome (BN273), with 273 brain regions .

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Abstract

The invention relates to a brain function connection network analysis method based on a resting state functional magnetic resonance image, and the method is characterized in that the method comprises the following steps: S1, obtaining an rs-fMRI image, and carrying out the preprocessing of the rs-fMRI image; s2, segmenting the rs-fMRI image by adopting three brain templates with different scales, and constructing three graphs G1, G2 and G3; s3, according to the obtained three graphs G1, G2 and G3, hidden feature representation of the graphs is learned by adopting a GNN module, and preliminary prediction labels L1, L2 and L3 are obtained; obtaining a final prediction label after voting; s4, performing significance analysis on a pooling result of the GNN module in the step S3, and obtaining a brain region with significant difference in the functional network; and S5, mapping the prominent brain region of the functional network to the Yeo 7 brain functional network map, and obtaining the mapped functional network connection, namely the individual difference functional sub-network. According to the method, the brain network is constructed by using the three different scales of brain templates, the integrated learning strategy is adopted, the multi-scale information of the multiple brain templates is fully fused, and the model performance is improved.

Description

technical field [0001] The invention relates to the field of brain functional connection network construction, in particular to a brain functional connection network analysis method based on resting state functional magnetic resonance images. Background technique [0002] The construction and analysis of brain functional connectivity network is the basic link in the study of brain function and brain diseases. Resting-state functional magnetic resonance imaging (rs-fMRI) captures the spontaneous activity of neurons by observing changes in blood oxygen levels in the brain; the subject remains stationary during the scan, requiring no complex experimental design. Through rs-fMRI image analysis, it is possible to study the mechanism of brain operation non-invasively and comprehensively. [0003] One of the existing rs-fMRI image analysis methods is the brain functional connectivity analysis method based on graph theory. The brain is one of the most complex networks. The develo...

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Application Information

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IPC IPC(8): G06T7/00G06T7/11G06V10/20G06V10/46G06V10/764G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06T7/0012G06T7/11G06N3/08G06T2207/10088G06T2207/20081G06T2207/20084G06N3/045G06F18/24323
Inventor 杨明静胡光辉
Owner FUZHOU UNIV
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