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Time series analysis method of nuclear magnetic resonance for brain functions based on constrained optimization

A technology of time series analysis and nuclear magnetic resonance, applied in medical science, sensors, diagnostic recording/measurement, etc., to achieve the effect of flexible expansion of the method

Inactive Publication Date: 2005-06-15
INST OF AUTOMATION CHINESE ACAD OF SCI
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  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

Compared with the general linear model, although the deconvolution model improves the sensitivity to a certain extent, studies have shown that the hemodynamic changes between each stimulus (trial) of the human brain are different. The product model is useless

Method used

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  • Time series analysis method of nuclear magnetic resonance for brain functions based on constrained optimization
  • Time series analysis method of nuclear magnetic resonance for brain functions based on constrained optimization
  • Time series analysis method of nuclear magnetic resonance for brain functions based on constrained optimization

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Experimental program
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Effect test

Embodiment

[0038] 1. Estimate the hemodynamic function of a single pixel

[0039] The selected time series such as figure 2 . There are 13 stimuli and 91 time points.

[0040] We first estimate the hemodynamic function of the pixel, and the result is: [3.26 5.38 0.50 -3.92 -3.96 -4.46 -2.57]

[0041] 2. Estimate the hemodynamic function of different stimuli

[0042] Using the hemodynamic function of the pixel estimated in the first step and constrained optimization (see formula (2)), we can obtain the hemodynamic function of each stimulus (see image 3 ).

[0043] 3. Statistical hypothesis testing

[0044] Using formula (3), the calculated F statistic value is 18.53, which obeys the F(7,195) distribution, and the corresponding probability value is 2.5618e-018. In general, if the p-value is 0.01. Then this pixel is the active pixel. In addition, compared with the traditional inverse convolution method, the following table is obtained:

[0045] Method

[0046] By comparison, the F st...

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Abstract

An NMR time sequence method based on constrained optimization for testing the cerebral functions and diagnosing cerebral diseases includes acquiring functional NMR time sequence, reverse convolution operation to estimate the hamodynamic function of single pixel, estimating the hamadynamic function to different stimulations, optimizing the hamodynamic function, and statistical tentation examining to each pixel one by one.

Description

Technical field [0001] The present invention relates to the field of nuclear magnetic resonance technology, in particular to a brain function nuclear magnetic resonance time series analysis method based on constraint optimization, which is used for preoperative brain function positioning, brain disease diagnosis and post-treatment evaluation, and brain science research in medical clinics The brain function area positioning and the function connection analysis of the brain function area in the brain function area belong to the intelligent information processing technology. Background technique [0002] Since the birth of functional magnetic resonance imaging fMRI technology, fMRI time series analysis has always been a hot research direction of fMRI researchers in various countries. Generally, fMRI time series analysis algorithms can be divided into two categories: model-driven and data-driven. Due to the physiological rationality and ease of use of the data-driven method, it has g...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/055
Inventor 吕英立蒋田仔臧玉峰
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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