method for detecting fMRI brain network dynamic co-variations

A brain network and dynamic technology, applied in the field of biomedical image pattern recognition, can solve problems such as inability to explore diseases well and difficulty in obtaining them

Active Publication Date: 2019-03-26
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Abstract
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Problems solved by technology

At present, studies have used sliding windows to construct brain dynamic networks. However, the current method is difficult to obtain longitudinal data, and cannot well explore the relationship between diseases and human brain cognitive functions and brain activity patterns.

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  • method for detecting fMRI brain network dynamic co-variations
  • method for detecting fMRI brain network dynamic co-variations
  • method for detecting fMRI brain network dynamic co-variations

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Embodiment Construction

[0027] In order to make the purpose, technical solutions and advantages of the present invention clearer, the following technical solutions in the present invention are clearly and completely described. Obviously, the described embodiments are some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0028] The invention provides a method for detecting dynamic covariance of fMRI brain networks, which belongs to the technical field of biomedical image pattern recognition, and specifically relates to a method for detecting dynamic covariance of brain functional networks based on functional magnetic resonance time series. Resonance (fMRI) data constructs a brain functional network, and then arranges different network matrices in order according to certain basis (...

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Abstract

The invention provides a method for detecting fMRI brain network dynamic covariations. The method comprises the following steps of: obtaining a sample; Firstly, constructing a brain functional networkby utilizing functional magnetic resonance data; according to a certain basis (factors such as age, disease course length, education degree and the like), different network matrixes are arranged in sequence;obtaining a cross-tested network matrix sequence; then, a sliding window method is used for researching a covariant relationship between ROI brain regions which cross a tested object; and obtaining a series of covariant matrixes, and depicting the difference of the brain interval collaborative activity modes under the trans-tested scale is by calculating mathematical indexes for describing covariant relationship variability or through statistical inspection, so that the interactive relationship between brain regions in the network can be better understood.

Description

technical field [0001] 本方法属于生物医学图像模式识别技术领域,具体涉及一种探测fMRI脑网络动态协变的方法。 Background technique [0002] Functional magnetic resonance imaging (fMRI) technology provides us with a non-invasive way to observe the brain, which can well reflect the functional activities of the brain by using blood oxygen level-dependent (BOLD) signals. The connection between various parts of the human brain is very intricate and has a certain special pattern structure. In recent years, the concept of brain connectome (brain connectome) has been proposed and developed rapidly, and more and more researches have started from the brain network. 角度来考量大脑的功能活动、结构特征等。 The current brain science has changed from the previous division of the brain into independent functional areas to explore how each brain area influences each other and changes in the synergistic relationship. At present, studies have used sliding windows to construct brain dynamic networks. However, the current methods are difficult to obtain l...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/32G06K9/62
CPCG06V10/25G06F18/2411
Inventor 廖伟孟耀陈华富
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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