STN-based autism brain magnetic resonance image visualization method

A technology of magnetic resonance images and nuclear magnetic resonance images, which is applied in the field of visualization of autistic brain magnetic resonance images based on STN, can solve the problems of lack of input image invariance and small transformation range

Pending Publication Date: 2021-02-26
HUBEI UNIV OF TECH
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Problems solved by technology

Convolutional neural networks define a very powerful class of models, but are still limited by the lack of invariance to input images d

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  • STN-based autism brain magnetic resonance image visualization method
  • STN-based autism brain magnetic resonance image visualization method
  • STN-based autism brain magnetic resonance image visualization method

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Embodiment Construction

[0049] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0050] An STN-based visualization method for magnetic resonance images of the autistic brain, the specific method is as follows:

[0051] 1) Collect brain MRI images of autistic patients as training samples;

[0052] 2) Use the training samples to train the STN model to obtain transformed images;

[0053] 21) Construct the STN model and initialize the network parameters randomly;

[0054] Construct the STN model, such as figure 1 , the STN model includes three parts: localization network (Localisation Network), grid generator (Grid Generator), and sampler (Samper). Among them: Localisation Network is a small convolutional neural network, and the input feature map U passes through multiple The convolutional layer and the pooling layer, and then through the fully connected and regression layers, generate the spatial transformation pa...

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Abstract

The invention discloses an STN-based autistic brain magnetic resonance image visualization method, which comprises the following steps: acquiring a brain nuclear magnetic resonance image of an autistic patient as a training sample, and training an STN model by using the training sample to obtain a transformed image; and training the transformed image according to the STN model, and transmitting thetransformed image to a convolutional neural network for training, so that visualization of the brain nuclear magnetic resonance image of the autistic patient is achieved. According to the STN model,the autism brain magnetic resonance image is processed on the basis of the convolutional neural network model, automatic recognition and detection are achieved, the visualization effect is good, the STN model is obviously improved compared with the convolutional neural network model, and medical researchers can be assisted in quantitative analysis and research conveniently.

Description

technical field [0001] The invention belongs to the technical field of nuclear magnetic resonance image disease visualization, and in particular relates to an STN-based visualization method for brain magnetic resonance images of autism. Background technique [0002] In recent years, the field of computer vision has undergone earth-shaking changes and has continued to move forward. The convolutional neural network model has achieved good results in classification, target detection, image segmentation, and action recognition. Convolutional neural networks define a very powerful class of models, but are still limited by the lack of invariance to input images due to the usually small transformation range of max pooling invariance to translation, scaling, rotation and more general deformations. [0003] In this case, the spatial transformation network (STN, Spatial Transformer Network) module can be included in the existing convolutional neural network architecture. Unlike the po...

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Application Information

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IPC IPC(8): G16H30/40G06T7/00
CPCG16H30/40G06T7/0012G06T2207/10088G06T2207/20081G06T2207/20084G06T2207/30016
Inventor 柯丰恺刘欢平赵大兴孙国栋
Owner HUBEI UNIV OF TECH
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