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Brain image processing method, computer equipment and readable storage medium

A processing method and brain image technology, applied in the field of images, can solve the problem of inability to classify FMRI signals, and achieve the effects of rapid analysis, improved accuracy, and improved efficiency

Active Publication Date: 2020-01-24
SHANGHAI UNITED IMAGING INTELLIGENT MEDICAL TECH CO LTD
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Based on this, it is necessary to provide a brain image processing method, computer equipment and readable storage medium for the problem that traditional technologies cannot classify FMRI signals more accurately

Method used

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  • Brain image processing method, computer equipment and readable storage medium
  • Brain image processing method, computer equipment and readable storage medium
  • Brain image processing method, computer equipment and readable storage medium

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Embodiment Construction

[0057] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

[0058] The brain image processing method provided by the embodiment of the present application can be applied to such as figure 1 computer equipment shown. The computer device includes a processor and a memory connected through a system bus, and a computer program is stored in the memory. When the processor executes the computer program, the steps of the following method embodiments can be performed. Optionally, the computer device may also include a network interface, a display screen and an input device. Wherein, the processor of the computer device is used to provide ...

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Abstract

The invention relates to a brain image processing method, computer equipment and a readable storage medium. The method comprises the following steps: acquiring a brain function image; obtaining time domain feature information of each brain region from the brain function image and performing Fourier transform to obtain node features of each brain region, wherein the node characteristics comprise frequency domain real part features and frequency domain imaginary part features; according to the node characteristics of each brain region, obtaining connection information of each brain region, and taking the connection information as connection between the nodes; constructing a graph characteristic matrix by the node characteristics and the connection among the nodes; and inputting the graph characteristic matrix into a training model to obtain an analysis result, wherein the training model is the model obtained by inputting the sample graph characteristic matrix constructed by the sample brain function image into a graph network for training. According to the method, the frequency domain features obtained by performing Fourier transform on the time domain feature information of each brain region are used as the node characteristics of each brain region, so that the noise in the brain function image can be better distinguished, and the accuracy of the obtained analysis result is improved.

Description

technical field [0001] The present invention relates to the image field, in particular to a brain image processing method, computer equipment and a readable storage medium. Background technique [0002] Functional Magnetic Resonance Imaging (FMRI) detects brain activity by measuring blood oxygen-level dependent (BOLD) in the blood. Clinically, there are mainly two different ways to analyze FMRI signals, one is to analyze the connection characteristics of the brain from the perspective of brain network by calculating the correlation of time series signals between two brain regions; the other is to extract The low-frequency amplitude (Amplitude of low frequency fluctuation, ALFF), local consistency (Regional homogeneity, ReHo) and other indicators of the FMRI signal are obtained, and the FMRI signal is classified using a simple classifier, such as a support vector machine, a decision tree, etc., so as to classify the brain activities are detected. In recent years, with the d...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0476A61B5/00
CPCA61B5/7257A61B5/7264A61B2576/026A61B5/369
Inventor 邢潇丹石峰
Owner SHANGHAI UNITED IMAGING INTELLIGENT MEDICAL TECH CO LTD
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