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Method for detecting brain network function connectivity lateralization based on modality fusion

A laterality, brain technology, applied in the field of image processing, can solve problems such as less time dimension

Active Publication Date: 2013-10-09
INST OF AUTOMATION CHINESE ACAD OF SCI
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Problems solved by technology

However, previous studies on brain network lateralization basically only used functional magnetic resonance imaging to measure brain active regions. Although the research results have high spatial resolution, they provide less information in the temporal dimension.

Method used

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  • Method for detecting brain network function connectivity lateralization based on modality fusion
  • Method for detecting brain network function connectivity lateralization based on modality fusion
  • Method for detecting brain network function connectivity lateralization based on modality fusion

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Embodiment Construction

[0015] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in combination with specific examples and with reference to the accompanying drawings.

[0016] The present invention mainly uses the characteristics of high spatial resolution of functional magnetic resonance imaging (fMRI) to locate the spatial three-dimensional coordinate information of the brain regions in the left and right hemispheres of the brain on the fMRI image, and then extract the information from the magnetoencephalography (MEG) data. The high-resolution time series corresponding to the above-mentioned brain regions enables high-resolution and accurate detection of the laterality of the brain network in two dimensions of time and space.

[0017] figure 1 It is a specific embodiment of a brain network laterality detection method based on magnetic resonance and magnetoencephalography modal fusion invo...

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Abstract

The invention relates to a method for detecting brain network function connectivity lateralization based on modality fusion. The method includes the steps that first, pretreatment is conducted on an fMRI image, and three-dimensional space coordinate information of brain areas inside a left hemisphere and a right hemisphere of a brain network is extracted; then, corresponding time series information is extracted from pretreated MEG data based on the three-dimensional space coordinate information of the brain areas extracted through the fMRI image; afterwards, the time series of the brain areas extracted from the MEG data can be used for analyzing the function connectivity between the brain areas; ultimately, the lateralization index of the function connectivity between the brain areas of the brain network is calculated. The method is an effective method for detecting the brain network function connectivity lateralization based on magnetic resonance and magnetoencephalogram modality fusion, and the method can detect the brain network function connectivity lateralization more completely and comprehensively compared with a traditional detection method which only uses the fMRI image.

Description

technical field [0001] The invention belongs to the field of image processing, and in particular relates to a detection method for studying the laterality of brain network functional connection by using brain function imaging technology. In particular, it relates to the detection of lateralization of functional connectivity of brain networks using functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) modality fusion. Background technique [0002] With the advancement of science and technology, non-invasive brain functional imaging technology is developing rapidly, providing a broad stage for us to use a variety of imaging techniques for brain cognition research. Due to the different imaging mechanisms, each imaging technique has corresponding advantages and disadvantages, so no imaging modality is suitable for all experimental research or clinical applications. Up to now, functional Magnetic Resonance Imaging (fMRI) has been widely used in the diagno...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T5/00A61B5/055
Inventor 田捷尤优博董迪杨鑫刘振宇卫文娟
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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