Neuropathology hub node identification method combining pathology and topological information

A neuropathological and topological information technology, applied in the field of neuropathological hub node identification, can solve the problems of neuropathological load difference, ignore the spatial distribution pattern of neuropathological load, etc., achieve the effect of prevention and treatment promotion, and achieve consistent distribution.

Pending Publication Date: 2022-03-01
HANGZHOU DIANZI UNIV
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Problems solved by technology

While this two-step approach has the advantage of being intuitive, it ignores the spatial pattern of neuropathological load re...

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  • Neuropathology hub node identification method combining pathology and topological information
  • Neuropathology hub node identification method combining pathology and topological information
  • Neuropathology hub node identification method combining pathology and topological information

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Embodiment Construction

[0057] The method of the present invention will be further described below in conjunction with the accompanying drawings.

[0058] Such as figure 1 As shown, a neuropathological hub node identification method that combines pathology and topology information, the steps are as follows:

[0059] Step (1), determine the basic mathematical model of the brain network:

[0060] In the field of neuroscience, each brain network can use a graph coded representation. The vertex set V of the brain network = {v 1 ,v 2 , v 3 ,...,v N}, where v i Indicates the i-th vertex (brain region) in the brain network, and N=|V| indicates the total number of vertices contained in each brain network. Anatomical Connectivity Matrix is an N×N weighted adjacency matrix, w ij represents a pair of brain regions (v i , v j ), the value of which is determined by the number of white matter fibers that physically connect the corresponding brain regions. For the adjacency matrix W, calculate its sy...

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Abstract

The invention discloses a neuropathology hub node identification method combining pathology and topological information. The method comprises the following steps: firstly, determining a basic mathematical model of a brain network; then defining a neuropathologic potential and a neuropathologic potential difference, and then defining a neuropathologic potential difference of the whole brain network; constructing an energy function of the neuropathology hub recognition, and determining an optimization method of the neuropathology hub recognition; finally, real nerve image data are preprocessed, and an optimization algorithm is executed to obtain a neuropathology hub; according to the method, the effect of the neuropathology hub in the brain network topological structure and the characteristic expression of the neuropathology load distributed at the neuropathology hub are analyzed in a combined mode, the hub node with the high neuropathology potential is recognized, and the limitation that only topological characteristics of the hub node in the network structure are considered in a traditional hub recognition method is solved.

Description

technical field [0001] The invention relates to a hub node identification method of a brain network, in particular to a neuropathological hub node identification method combining pathology and topology information. Background technique [0002] As a complex neurodegenerative disease, Alzheimer's disease is a syndrome of disconnection between neurons, that is, due to neuropathological damage, the connection between neurons is gradually reduced. Often, neuropathological changes precede the onset of AD dementia. Therefore, quantification of neuropathological burden is crucial for the early diagnosis of AD. Advances in imaging technology have allowed us to quantify pathological burden in vivo by positron emission tomography (PET), such as Amyloid-PET (A biomarker), Tau-PET (T biomarker), and other typical AD biomarkers things. To better understand the pathological mechanisms of AD, an increasing number of studies have focused on the spatial patterns of neuropathological burde...

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Application Information

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IPC IPC(8): G06T7/00G06T7/10G06T7/38
CPCG06T7/0012G06T7/10G06T7/38G06T2207/10104G06T2207/10088G06T2207/30016
Inventor 杨德富李文超沈晨雨颜成钢孙垚棋肖芒吴欢
Owner HANGZHOU DIANZI UNIV
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