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Brain structure network connection optimization method based on random partitioning model

A random block model and optimization method technology, applied in the field of image processing, can solve the problem of low reliability of the brain structure network, achieve high application value, high reliability, and eliminate measurement errors

Active Publication Date: 2016-12-21
TAIYUAN UNIV OF TECH
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Problems solved by technology

[0003] In order to solve the problem of low credibility of the brain structure network constructed by the existing brain structure network construction method, the present invention provides a brain structure network connection optimization method based on a random block model

Method used

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  • Brain structure network connection optimization method based on random partitioning model
  • Brain structure network connection optimization method based on random partitioning model
  • Brain structure network connection optimization method based on random partitioning model

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Embodiment Construction

[0015] This implementation takes monkey brain data as an example for illustration. All subjects were scanned by 3T magnetic resonance equipment (Siemens Trio 3-Tesla Scanner, Siemens, Erlangen, Germany) for magnetic resonance diffusion weighted scanning. river monkey.

[0016] A brain structure network connection optimization method based on a random block model, the method is implemented by the following steps:

[0017] Step S1: preprocessing the MRI diffusion weighted image, and then performing region segmentation on the preprocessed MRI diffusion weighted image according to the selected standardized brain atlas;

[0018] Step S2: Use the fiber tract tracking algorithm to map the preprocessed MRI diffusion-weighted images to the selected standardized brain atlas, and then calculate the number of fiber tracts in the two brain intervals according to the end conditions of the fiber tract tracking, thus Obtain the number matrix of fiber tracts in the brain region;

[0019] Ste...

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Abstract

The invention relates to an image processing technology, and specifically relates to a brain structure network connection optimization method based on a random partitioning model. The problem that a brain structure network built using the existing brain structure network building method is of low credibility is solved. The brain structure network connection optimization method based on a random partitioning model is implemented according to the following steps: S1, preprocessing a magnetic resonance diffusion weighted image, and partitioning the preprocessed magnetic resonance diffusion weighted image; S2, calculating the number of fiber bundles of every two brain intervals; S3, binarizing a fiber bundle number matrix of the brain intervals according to a threshold; S4, building a brain structure central network model based on multiple brain structure network model samples; S5, calculating the credibility of connection in the brain structure central network model; and S6, rebuilding and optimizing the brain structure central network model. The method is suitable for brain structure network building.

Description

technical field [0001] The invention relates to image processing technology, in particular to a brain structure network connection optimization method based on a random block model. Background technique [0002] As a combination of MRI diffusion weighted imaging (DWI) technology and complex network theory, the construction method of brain structure network has become one of the hotspots in the field of brain science. However, under the current technical conditions, the brain structure network construction method is affected by the measurement error in the data collection link, resulting in the general problem of low reliability of the constructed brain structure network, which seriously affects its application value. Based on this, it is necessary to invent a new method for optimizing the connection of brain structural networks to solve the above-mentioned problems existing in the existing methods for constructing brain structural networks. Contents of the invention [00...

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Application Information

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IPC IPC(8): G06T11/00
CPCG06T11/005G06T11/008
Inventor 郭浩曹锐陈永乐相洁李海芳陈俊杰
Owner TAIYUAN UNIV OF TECH
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