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Structure and function magnetic resonance image united classification method based on network analysis

A technology of functional magnetic resonance and network analysis, applied in the field of image processing, can solve problems such as classification performance degradation and unreasonable assumptions, and achieve the effect of accurate classification

Active Publication Date: 2013-04-03
INST OF AUTOMATION CHINESE ACAD OF SCI
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Problems solved by technology

However, such an assumption is unreasonable in many cases
Brain magnetic resonance images of people in different states will be disturbed by many factors. Traditional classification methods do not classify brain magnetic resonance images according to the inherent properties of the brain, which will lead to a decline in classification performance.

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  • Structure and function magnetic resonance image united classification method based on network analysis
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  • Structure and function magnetic resonance image united classification method based on network analysis

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Embodiment Construction

[0016] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0017] The joint classification method of structural and functional magnetic resonance images based on network analysis is a new classification method of magnetic resonance images. The method first establishes a structural and functional brain network model, calculates the characteristic path length, cluster degree and network centrality of the brain network to represent different image patterns; then uses these network parameters to train an adaptive boosting (adaboost) classification device.

[0018] refer to figure 1 , according to a kind of human brain MRI image classification method of the present invention, can determine the category of test sample image according to training sample image, concrete implementation s...

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Abstract

The invention provides a structure and function magnetic resonance image united classification method based on network analysis. The method includes firstly, establishing a structure and function brain network model, calculating characteristic path length, an agglomeration degree and a network centrality of a brain network to represent different image models, and then training a self-adaption improving classifier by using network parameters. The structure and function magnetic resonance image united classification method can use as many messages as possible in a magnetic resonance image, the brain network parameters can reflect brain activities in nature, and simultaneously, a technology of multiple classifiers is used, so that the defect that inherent attributes of the brain activities can not be reflected by traditional classification methods is made up, and the brain magnetic resonance image can be accurately classified.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a joint classification method of structural and functional magnetic resonance images based on network analysis. Background technique [0002] Magnetic Resonance Imaging (MRI) has been widely used in the diagnosis and treatment of neurological diseases due to its high spatial and temporal resolution and non-invasive characteristics. The brain is a complex system, and magnetic resonance images of the brain respond to stimulating conditions or lesions. It is an important application of computer-aided analysis to use image classification methods to calculate the possibility of magnetic resonance images having certain attributes, or to automatically distinguish the category attributes of images. [0003] Traditional MRI image classification methods mainly include region of interest (ROI) method and voxel method. The classification method of the region of interes...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/66
Inventor 田捷刘振宇刘建刚
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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