Neural image classification method, computer terminal and computer readable storage medium

An image classification and neural technology, applied in the field of medical image processing, can solve the problems of low efficiency, time-consuming and laborious, relatively high technical level requirements, and achieve the effect of solving the impact and improving the classification performance.

Inactive Publication Date: 2019-08-09
SHENZHEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] An existing method for classifying neuroimaging is the manual classification method. Doctors usually perform manual diagnosis based on personal medical experience combined with neuroimaging. Another method to classify neural image

Method used

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  • Neural image classification method, computer terminal and computer readable storage medium
  • Neural image classification method, computer terminal and computer readable storage medium
  • Neural image classification method, computer terminal and computer readable storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0057] figure 1 A schematic flowchart of a neural image classification method provided by the first embodiment of the present invention is shown.

[0058] The neural image classification method includes the following steps:

[0059] In step S110, a connection matrix corresponding to the neuroimage is generated according to the connection relationship between the brain regions in the neuroimage.

[0060] In this embodiment, the neuroimage is a functional Magnetic Resonance Imaging (fMRI) neuroimage of the brain. In some other embodiments, the neuroimaging may also be electroencephalography (Electroencephalography, EGC), magnetoencephalography (Magnetoencephalography, MEG) and other neuroimaging.

[0061] Specifically, the neuroimage can be collected by a magnetic resonance acquisition device. In this embodiment, the brand of the acquisition device can be General Electric (GE), Siemens (SIEMENS), or Philips (PHILIPS). In some other embodiments, the brand of the acquisition de...

Embodiment 2

[0141] Figure 7 A schematic structural diagram of a neuroimage classification device provided by the second embodiment of the present invention is shown. This neuroimage classification device 400 corresponds to the neuroimage classification method of Embodiment 1. Any optional items in Embodiment 1 are also applicable to this embodiment, and will not be described in detail here.

[0142] The neuroimage classification device 400 includes a generation module 410 , an extraction and formation module 420 , a construction module 430 , a training module 440 and a classification module 450 .

[0143] The generation module 410 is configured to generate a connection matrix corresponding to the neuroimage according to the connection relationship between the brain regions in the neuroimage.

[0144] The extraction and formation module 420 is configured to extract a predetermined number of element values ​​in the connection matrix according to a predetermined extraction rule and form a...

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Abstract

The invention discloses a neural image classification method, a computer terminal and a computer readable storage medium. The method comprises the steps of generating a connection matrix correspondingto a neural image according to a connection relationship between brain regions in the neural image; extracting a predetermined number of element values from the connection matrix according to a predetermined extraction rule and forming a tested feature vector; taking the plurality of tested feature vectors as nodes, and constructing a feature map according to similar characteristics among the non-image information corresponding to each node; initializing a pre-established classification model according to the feature map, and training the initialized classification model according to the tested feature vector; and classifying the neural images according to the trained classification model. According to the technical scheme provided by the invention, the feature map is constructed throughthe similarity between the non-image information of each tested feature vector, and the established classification model is initialized according to the feature map, so that the individual differenceof the tested object and the influence of acquisition equipment on the classification result are effectively solved, and the classification performance is improved.

Description

technical field [0001] The present invention relates to the technical field of medical image processing, in particular to a neural image classification method, a computer terminal and a computer-readable storage medium. Background technique [0002] With the rapid development of medical image processing technology, the demand for classification of neuroimages (such as identifying Alzheimer's disease AD, mild cognitive impairment MCI, etc. through neural influence) is becoming more and more extensive. [0003] An existing method for classifying neuroimaging is the manual classification method. Doctors usually perform manual diagnosis based on personal medical experience combined with neuroimaging. Another method to classify neural images is a classification method based on deep learning (such as convolutional neural network). Deep learning provides a new way of thinking for graph analysis. It is not suitable for images with irregular structure and non-Euclidean space. Cont...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06K9/62
CPCG06T7/0012G06T2207/20081G06T2207/30016G06F18/24G06F18/214
Inventor 雷柏英赵鑫汪天富倪东
Owner SHENZHEN UNIV
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