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Blood sample level dependence functional magnetic resonance signal fluctuating frequency clustering analysis method

A technology of functional magnetic resonance and oscillation frequency, which is applied in the field of medical image processing and analysis, and can solve problems such as the lack of data-driven frequency analysis methods

Inactive Publication Date: 2014-05-07
NANTONG NANDA DIMENSIONAL IMAGE PASS TECH
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Problems solved by technology

[0008] The technical problem to be solved by the present invention is to overcome the above-mentioned defects, provide a blood sample level-dependent fMRI signal oscillation frequency clustering analysis method, solve the problem that the current fMRI research field lacks a data-driven frequency analysis method, and provide basic science and Clinical research provides new imaging analysis methods, and at the same time provides new quantitative indicators and physiological markers for clinical disease diagnosis and pathological mechanism research

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  • Blood sample level dependence functional magnetic resonance signal fluctuating frequency clustering analysis method
  • Blood sample level dependence functional magnetic resonance signal fluctuating frequency clustering analysis method
  • Blood sample level dependence functional magnetic resonance signal fluctuating frequency clustering analysis method

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Embodiment

[0058] The blood sample level-dependent fMRI signal oscillation frequency cluster analysis method comprises the following steps:

[0059] Step 1, preprocessing and analyzing the resting state data collected from the MRI machine.

[0060] Step 2, using the Hilbert-Huang transform, the Hilbert-Huang transform includes two steps of Empirical Mode Decomposition (EMD) and Hilbert Transform (HT), decompose the preprocessed signal to obtain the eigenmodes of different frequencies state function.

[0061] Step three, calculate various quantitative indicators of the intrinsic mode function (IMF) at different frequencies, such as energy, Hilbert weighted frequency (HWF), local consistency () and so on.

[0062] Step 4, clustering different voxels in the brain based on the above quantitative indicators. Statistical analysis of the above different indicators.

[0063] In this embodiment, the specific implementation steps of step 1) preprocessing and analyzing the BOLD-fMRI signal data ...

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Abstract

The invention discloses a blood sample level dependence functional magnetic resonance signal fluctuating frequency clustering analysis method which is characterized by comprising the following steps: step 1, pretreatment analysis is performed on resting state data collected from a magnetic resonance machine; step 2: Hilbert-Huang transform is adopted for decomposing the pretreated signals, so as to obtain intrinsic mode functions with different frequencies; the Hilbert-Huang transform comprises two steps of empirical mode decomposition and Hilbert transform; step 3, quantitative indexes of different frequency components are calculated; step 4, clustering of different voxels in a brain is performed by taking the quantitative indexes in the step 3, as a basis for classification and statistical analysis to the different indexes is performed. The method solves the problem of insufficiency of data drive frequency analysis methods in the fMRI research field, an iconography analytical method is provided for basic science and clinical researches and meanwhile new quantitative indexes and physiological markers are provided for clinical disease diagnosis and pathological mechanisms.

Description

technical field [0001] The invention belongs to the technical field of medical image processing and analysis, and in particular relates to a blood sample level-dependent functional magnetic resonance signal oscillation frequency cluster analysis method. Background technique [0002] Functional magnetic resonance imaging of blood oxygen level-dependent effects can non-destructively detect and localize brain functional areas, and is a new technology developed in neuroimaging. It can not only reflect brain function and physiological changes, but also perform brain function positioning and integrate neuroanatomical and functional information, intuitively reflecting the neural mechanisms related to various diseases or cognitive tasks. [0003] Various physiological and psychological activities of the body are accompanied by the discharge activity of central neurons. The collective point activity of neurons leads to biochemical changes in the blood flow of nerves and surrounding ...

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Application Information

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IPC IPC(8): A61B5/055A61B5/145
Inventor 宋潇鹏张毅刘一军
Owner NANTONG NANDA DIMENSIONAL IMAGE PASS TECH
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