Brain image classification method and storage medium

A classification method and brain image technology, which are applied in the field of brain image classification methods and storage media, can solve problems such as inaccurate classification of brain images, and achieve the effect of improving accuracy

Pending Publication Date: 2020-11-17
SHANGHAI UNITED IMAGING INTELLIGENT MEDICAL TECH CO LTD
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Problems solved by technology

[0004] However, traditional brain image classification methods have the problem of inaccurate classification of brain images.

Method used

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  • Brain image classification method and storage medium
  • Brain image classification method and storage medium
  • Brain image classification method and storage medium

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Embodiment Construction

[0058] 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.

[0059] The brain image classification method provided in the embodiment of the present application can be applied to such as figure 1computer 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 provi...

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Abstract

The invention relates to a brain image classification method and a storage medium. The method comprises the steps of obtaining a to-be-classified brain function image; obtaining a graph characteristicmatrix corresponding to the brain function image according to the brain function image; inputting the graph characteristic matrix into a characteristic extraction sub-network of a preset image classification network to obtain characteristic information between brain regions in the brain function image; inputting the feature information between the brain regions into a clustering sub-network of animage classification network, clustering the brain regions, and clustering the brain regions into different brain loops; and inputting each brain loop into the classification sub-network of the imageclassification network to obtain a classification result of the brain function image. By adopting the method, the accuracy of the obtained classification result of the brain function image can be improved.

Description

technical field [0001] The present application relates to the technical field of image processing, in particular to a brain image classification method and a storage medium. Background technique [0002] With the development of neural network technology, a neural network with a special structure such as a graph structure, that is, a graph convolutional neural network (Graph Convolutional Network, GCN), has also been proposed. GCN learns the information in the graph structure by using the network model of deep learning, and has a good performance in classification. [0003] In the traditional technology, when classifying brain images, all the brains in the brain image are separated to obtain multiple regions of interest. By calculating the correlation between two regions of interest, the functional signal correlation is obtained, and the obtained The functional signal correlation of the brain is used as the connection strength between two regions of interest to form a whole-...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/55G06K9/62G06N3/04
CPCG06F16/55G06N3/044G06N3/045G06F18/2414
Inventor 邢潇丹石峰
Owner SHANGHAI UNITED IMAGING INTELLIGENT MEDICAL TECH CO LTD
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