Functional magnetic resonance image data classification method based on brain network modular structure characteristics

A technology of functional magnetic resonance and modular structure, which is applied in special data processing applications, electrical digital data processing, character and pattern recognition, etc., and can solve problems such as unsatisfactory classification results and inability to classify magnetic resonance images.

Inactive Publication Date: 2014-06-25
TAIYUAN UNIV OF TECH
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Problems solved by technology

Therefore, traditional classification methods cannot classify MRI images according to the inherent properties of the brain, so the classification effect is not ideal.

Method used

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  • Functional magnetic resonance image data classification method based on brain network modular structure characteristics
  • Functional magnetic resonance image data classification method based on brain network modular structure characteristics
  • Functional magnetic resonance image data classification method based on brain network modular structure characteristics

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Embodiment Construction

[0063] The present invention will be further described below in conjunction with the drawings and specific embodiments:

[0064] The present invention proposes a functional magnetic resonance image data classification method based on the structural characteristics of brain network modules. The brain network module structure is used to analyze the local aggregation characteristics of the network, reveal the potential relationship between structure and function, and effectively improve the data classification. accuracy.

[0065] The specific implementation process of the functional magnetic resonance image data classification method based on the structural characteristics of the brain network module of the present invention is as follows figure 1 As shown, including the following steps:

[0066] Step S1: preprocessing the resting state functional magnetic resonance image, and then segment the image according to the selected standardized brain atlas, and finally extract the average tim...

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Abstract

The invention discloses a functional magnetic resonance image data classification method based on brain network modular structure characteristics. According to the functional magnetic resonance image data classification method based on the brain network modular structure characteristics, network local gathering characteristics are described from the perspective of a modular structure, network collectivization characteristics are reflected, the potential relation between the structure and the function in the network is reflected, the defect that according to a traditional classification method, description of brain local characteristics is poor is overcome, and data classification accuracy is effectively improved.

Description

Technical field: [0001] The invention relates to a functional magnetic resonance image data classification method based on the structural characteristics of a brain network module. Background technique: [0002] Functional Magnetic Resonance Imaging (fMRI) is an imaging technology. Because of its non-invasiveness, high spatial resolution, and relatively simple use, it was quickly applied by researchers in neuroscience and psychology research. A breakthrough has been made. fMRI mainly studies brain activation by measuring blood oxygen level dependent signal (Blood Oxygenation Level Dependent, BOLD). BLOD mainly detects changes in blood oxygen in the human brain. When the brain nervous system is activated, it will cause changes in blood oxygen content in some areas of the brain. Changes in blood oxygen will cause local changes in the magnetic field, which in turn will cause MRI signals to occur. change. When the human brain is in different states, such as task stimulation or dis...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06F19/00
Inventor 相洁郭浩陈俊杰李海芳邓红霞王会青曹锐
Owner TAIYUAN UNIV OF TECH
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