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Brain network specific structure extraction method for Alzheimer's disease and mild cognitive impairment

A technology for Alzheimer's disease and mild cognitive impairment, which is applied in the field of AD and MCI brain network-specific structure extraction based on persistent coherent high-dimensional features, which can solve the problem of lack of threshold selection rules, large computational load, and lack of functional networks. Accuracy and other issues to achieve the effect of reducing the computational burden

Active Publication Date: 2020-04-24
HARBIN ENG UNIV
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Problems solved by technology

However, this method mainly has two shortcomings: (1) There is no clear threshold selection rule, and the functional network constructed based on a single threshold lacks accuracy, especially for the brain networks of patients with different clinical states; Interconnect patterns lead to excessive computational load

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  • Brain network specific structure extraction method for Alzheimer's disease and mild cognitive impairment
  • Brain network specific structure extraction method for Alzheimer's disease and mild cognitive impairment
  • Brain network specific structure extraction method for Alzheimer's disease and mild cognitive impairment

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Embodiment Construction

[0030] The specific embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0031] combine figure 1 , the present invention is realized like this:

[0032] Step 1: fMRI data preprocessing. Resting-state MRI scans were performed on subjects in three groups of AD, MCI and HC, and functional magnetic resonance images (.dcm) were obtained. The obtained brain image data were processed by time layer correction, head motion correction, standardization, smoothing, etc., and covariates such as white matter, cerebrospinal fluid, and head motion parameters in the brain image were removed, and BOLD (blood oxygen level dependent) in the corresponding voxel was extracted. ) time series signal.

[0033]Step 2: Brain network construction. Select the brain region segmentation template, physically segment the whole brain map, and determine the nodes in the brain network connection. On each node after the brain region is divided,...

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Abstract

The invention discloses a brain network specific structure extraction method for Alzheimer's disease and mild cognitive impairment. The method comprises the steps of 1, preprocessing functional magnetic resonance data; 2, constructing a brain network, partitioning whole brain functions and extracting a time sequence; 3, constructing a continuous homology model; 4, carrying out continuous homologyhigh-dimensional feature quantification, and performing statistical analysis on three groups of Landscapes of AD, MCI and HC through replacement inspection; 5, extracting a brain network specific structure; 6, outputting a result. According to the method, the problem of threshold selection in a graph theory method is avoided, the calculation burden can be effectively reduced, and the method is aninnovative method.

Description

technical field [0001] The invention relates to a method for extracting specific structures of AD and MCI brain networks, in particular to a method for extracting specific structures of AD and MCI brain networks based on persistent coherent high-dimensional features. Background technique [0002] Alzheimer's disease (AD) causes neurodegenerative brain damage and cognitive decline. Mild cognitive impairment (MCI) is a clinical state between normal aging amnesia (Health control, HC) and AD, in which MCI has a greater probability of further aggravating the disease and leading to AD. Therefore, the study of the pathological relationship between AD, MCI and HC is of great value for the discovery of pathogenic mechanisms, drug target research, etc., and can provide strong technical support for the research of early diagnosis and prediction of diseases. [0003] Research on the early diagnosis of Alzheimer's disease mainly focuses on the extraction of marker features, including ne...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H30/40G16H50/20G06K9/00
CPCG16H30/40G16H50/20G06F2218/08
Inventor 李金边晨源梁洪罗昊燃李延召段沛然李俞鑫闫岱孚曹骆龙江海龙
Owner HARBIN ENG UNIV
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