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Brain function magnetic resonance image classification-oriented TSK fuzzy system modeling method

A magnetic resonance image and fuzzy system technology, applied in the field of image processing, can solve problems such as failure to effectively use feature correlation characteristics

Active Publication Date: 2019-07-09
JIANGNAN UNIV
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Problems solved by technology

However, when the existing machine learning methods study image classification prediction, most of them assume that each feature is independent of each other, and fail to effectively use the correlation between features.

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  • Brain function magnetic resonance image classification-oriented TSK fuzzy system modeling method
  • Brain function magnetic resonance image classification-oriented TSK fuzzy system modeling method
  • Brain function magnetic resonance image classification-oriented TSK fuzzy system modeling method

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Embodiment Construction

[0038] 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.

[0039] The invention provides a TSK fuzzy system modeling method for classification of brain functional magnetic resonance images. This method first preprocesses and extracts features from brain fMRI images, then combines the relevant information of brain intervals with the TSK fuzzy system to construct a nonlinear classification method, and finally uses the hold-out method to verify the classification performance of the proposed classification method. The specific implementation steps are as follows:

[0040] Step S1: Perform preprocessing and brain region segmentation on the functional magnetic resonance image of the brain, and calculate the average time series of each brain region;

[0041] ① Remove the data of the fi...

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Abstract

The invention relates to a TSK fuzzy system modeling method for brain function magnetic resonance image classification, and belongs to the technical field of image processing. The method comprises thefollowing steps: S1, preprocessing a brain function magnetic resonance image; s2, calculating a Pearson correlation coefficient among the brain regions to obtain a symmetric matrix, taking a triangleon the symmetric matrix to unfold according to lines to obtain a sample feature vector, and representing the data of one picture by each column of the sample feature vector; s3, carrying out featureextraction on the sample feature vectors; and S4, constructing a classifier to classify the brain function magnetic resonance images, and solving a model used by the classifier by adopting an alternating optimization algorithm to complete image classification. According to the method, the nonlinear classifier is constructed based on the TSK fuzzy system, the correlation between the features is represented by using the undirected graph, and the brain function magnetic resonance images can be accurately classified.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a TSK fuzzy system modeling method for brain functional magnetic resonance image classification. Background technique [0002] Resting-state Functional Magnetic Resonance Imaging (rs-fMRI) technology can obtain high-resolution images by detecting blood oxygen levels under non-invasive and radiation-free conditions. An important tool for connectivity research. fMRI generally refers to magnetic resonance imaging based on blood oxygen level-dependent (BOLD), which reflects changes in magnetic resonance signals caused by changes in cerebral blood flow and cerebral blood oxygen caused by neural activity. brain activity. [0003] In recent years, various machine learning methods have been applied to the field of image classification. Among them, the fuzzy reasoning system based on clustering has been successfully applied in data-driven uncertain system modeling ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/34G06K9/40
CPCG06V10/30G06V10/267G06V2201/03G06F18/23G06F18/24Y02T10/40
Inventor 王骏张春香邓赵红石争浩张嘉旭祝继华王士同
Owner JIANGNAN UNIV
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