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A Classification Method of Human Brain Functional Network Based on Convolutional Neural Network

A convolutional neural network and functional network technology, applied in biological neural network models, neural architectures, instruments, etc., can solve the problems that convolutional neural network models cannot make full use of brain network topology information and affect the diagnosis of brain diseases. Achieve accurate brain disease diagnosis, reduce the risk of overfitting, and the method is reasonable and reliable

Active Publication Date: 2022-03-22
BEIJING UNIV OF TECH
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AI Technical Summary

Problems solved by technology

However, this method assumes that the edges from the same node have the same importance to different nodes. This assumption leads to the inability of the convolutional neural network model to fully utilize the topology information in the brain network, which affects the diagnosis of brain diseases. Effect

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  • A Classification Method of Human Brain Functional Network Based on Convolutional Neural Network
  • A Classification Method of Human Brain Functional Network Based on Convolutional Neural Network
  • A Classification Method of Human Brain Functional Network Based on Convolutional Neural Network

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Embodiment Construction

[0045] Take the simulation data set and the real fMRI data set as examples below to illustrate the specific implementation steps of the present invention: Step (1) obtain the resting state fMRI data and preprocess:

[0046] Step (1.1) Resting-state fMRI data acquisition: We obtained autism (Autismspectrum disorder, ASD) data from ABIDE (Autism Brain Imaging DataExchange, http: / / fcon_1000.projects.nitrc.org / indi / abide / ) for analysis , including the resting-state functional magnetic resonance imaging (rs-fMRI) data of 1112 subjects.

[0047] Step (1.2) Data preprocessing: In order to be able to easily reproduce and extend the method, all preprocessed data were obtained from the Preprocessed Connectomes Project (PCP, http: / / preprocessed-connectomes-project.org / abide / ). The PCP project publicly released and shared the preprocessed data of each site in ABIDE by four different preprocessing processes. The data used in the present invention are preprocessed by Data Processing Assist...

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Abstract

The invention discloses a method for classifying human brain function networks based on a convolutional neural network, which belongs to the field of brain science research. It is characterized in that it specifically includes the following steps: acquiring resting state fMRI data and preprocessing; generating simulation data; dividing data sets; and classifying human brain functional networks based on convolutional neural networks. The method of the present invention is based on a convolutional neural network, and uses independent weights (Element-wise Filters) to give unique weights to each edge and node of the human brain functional network data, thereby constructing a layer including "edge-to-node" and "node-to-graph". "layers of multilayer neural networks. The method of the present invention can better utilize the topological structure information of the human brain functional network data and perform feature expression, thereby improving the classification effect, and the method is reasonable and reliable, and can provide powerful help for the diagnosis of neuropsychiatric diseases.

Description

technical field [0001] The invention belongs to the field of brain science research. Specifically, the invention relates to a method for classifying human brain function networks based on convolutional neural networks. Background technique [0002] The human brain is one of the most important organs of the human body, containing a large number of neuron cells. Through the interaction between multiple neurons, neuron clusters or multiple brain regions, the human brain can complete various complex tasks. The structure and function of the human brain are extremely complex, far beyond our current cognitive capabilities. Therefore, it is undoubtedly very meaningful to explore and understand the working mechanism of the human brain and unravel the mystery of the brain. In recent years, with the continuous development of science and technology, more and more brain imaging techniques have been applied to brain research, such as magnetic resonance imaging (Magnetic Resonance Imagin...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N3/04G16H50/20
CPCG16H50/20G06N3/045G06F18/241G06F18/214
Inventor 邢新颖冀俊忠姚垚
Owner BEIJING UNIV OF TECH
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