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Method for classifying resting state functional magnetic resonance image data

A technology of functional magnetic resonance and image data, applied in the field of image processing, can solve the problem of low classification accuracy

Active Publication Date: 2022-08-05
TAIYUAN UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The purpose of the present invention is to provide a resting state functional magnetic resonance imaging data classification method based on the tree structure group lasso hypergraph U-Net model, and solve the problem of low classification accuracy of traditional magnetic resonance imaging data classification methods

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  • Method for classifying resting state functional magnetic resonance image data
  • Method for classifying resting state functional magnetic resonance image data
  • Method for classifying resting state functional magnetic resonance image data

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Embodiment Construction

[0016] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0017] Resting-state functional magnetic resonance imaging data classification method based on tree-structured group lasso hypergraph U-Net model, the method specifically includes the following steps:

[0018] Step S1: preprocessing the resting-state functional magnetic resonance image;

[0019] Step S2: performing regional segmentation on the preprocessed resting-state functional magnetic resonance image according to the selected sta...

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Abstract

The invention relates to an image processing technology, in particular to a resting-state functional magnetic resonance image data classification method, which is based on a tree structure group lasso hypergraph U-Net model, and is realized by adopting the following steps: S1, preprocessing a resting-state functional magnetic resonance image; s2, carrying out region segmentation on the preprocessed resting state functional magnetic resonance image according to the selected standardized brain map, and carrying out average time sequence extraction on each segmented brain region; s3, calculating the correlation degree between every two average time sequences of each brain region by adopting a Pearson's correlation method so as to obtain a correlation matrix, and selecting a correlation coefficient value of a triangle on the matrix as a brain network feature of each subject; the method is suitable for magnetic resonance image data classification.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a method for classifying resting state functional magnetic resonance imaging data. Background technique [0002] In recent years, neuroimaging techniques have provided many methods for exploring the connectivity of the human brain, especially network neuroscience, where the goal is to model brain connectivity as a network, where each node represents an anatomical region of interest (Regions of Interest). , ROI). Brain connections are generated from neuroimaging data, such as Magnetic Resonance Imaging (MRI) techniques, and are represented using functional, structural or morphological networks. Since cerebral psychiatric diseases affect the cognitive function of the brain, the purpose of neuroimaging is to classify the brain images of psychiatric patients and normal controls to help diagnose and detect brain diseases, and has been successfully used to assist in the diagn...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/11G06V10/764G06V10/774G06V10/82G06N3/04G06N3/08
CPCG06T7/0012G06T7/11G06V10/764G06V10/774G06V10/82G06N3/04G06N3/08G06T2207/10088G06T2207/20081G06T2207/20084G06T2207/30016
Inventor 杨艳丽刘涛郭浩李瑶
Owner TAIYUAN UNIV OF TECH
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