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Hilbert-Huang transform-based fMRI time-frequency domain dynamic network construction method

A dynamic network and construction method technology, applied in the field of medical image processing, can solve the problem of inaccurate capture of detailed information, and achieve the effect of simple algorithm parameter setting, reduced calculation amount, and simple wavelet transform

Active Publication Date: 2018-09-28
BEIJING UNIV OF TECH
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Problems solved by technology

Although the coherent method based on wavelet transform can capture high-frequency and low-frequency information at the same time, it needs to select the basis function in advance, and the capture of detailed information is not accurate enough.

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  • Hilbert-Huang transform-based fMRI time-frequency domain dynamic network construction method
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  • Hilbert-Huang transform-based fMRI time-frequency domain dynamic network construction method

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Embodiment Construction

[0048] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0049] Such as Figure 5 Shown, the present invention comprises the following steps:

[0050] Step 1, input the original image.

[0051] Step 2, preprocessing the original image.

[0052] DPARSF software was used to preprocess fMRI data, mainly for time layer correction, removal of head motion and artifacts, registration to structural images, normalization, smoothing, filtering, and removal of physiological noise.

[0053] Step 3, use GICA to extract brain regions and time series based on the strong functional connections of the whole brain.

[0054] figure 1 The representation diagram of GICA parameter setting, providing detailed parameter setting of GICA analysis;

[0055] Step 4, constructing a dynamic network in the time-frequency domain of fMRI based on HHT.

[0056] Step 5, analyze and study the changing state of the network in the time-frequency ...

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Abstract

The invention discloses a Hilbert-Huang transform-based fMRI time-frequency domain dynamic network construction method. The method comprises the steps that an original image is input; the original image is preprocessed; whole brain strong function connection-based brain regions and time sequences corresponding to the brain regions are extracted; the time sequences are subjected to post-processing;an HHT-based fMRI time-frequency domain dynamic network is constructed; and change models of the network are analyzed and studied in the time frequency domain. According to the method, by adopting the Hilbert-Huang transform algorithm, basis functions can be adaptively generated according to the data, and therefore inaccurate results generated by the fact that inappropriate basis functions are selected in advance are avoided.

Description

technical field [0001] The invention belongs to the field of medical image processing, and relates to a dynamic network algorithm in the time-frequency domain of fMRI (functional Magnetic Resonance Image, functional magnetic resonance imaging) in a resting state, mainly using the Hilbert-Huang transform algorithm to construct a dynamic network in the time-frequency domain . Background technique [0002] So far, most fMRI-based functional connectivity studies have assumed that the statistical interdependence patterns of signals between distant brain regions are fixed, such as correlations, covariances, and interactions of time series in different regions. The state is recorded throughout the entire period of the resting state experiment. Under this assumption, studies of brain function at large-scale scales have yielded remarkable results that describe complex spatiotemporal averaging phenomena. [0003] However, human brain connections are most likely to be dynamic, time-d...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T11/00
CPCG06T7/0012G06T11/005G06T11/008G06T2207/10088G06T2207/20048
Inventor 张馨杨春兰吴水才
Owner BEIJING UNIV OF TECH
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