Brain age prediction method and device based on 3D convolutional neural network

A convolutional neural network and prediction method technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve the problems of inaccurate prediction of children's brain age and information loss, and solve the problem of inaccurate prediction of children's brain age. , the effect of improving the accuracy

Inactive Publication Date: 2019-12-10
BEIJING SHENRUI BOLIAN TECH CO LTD
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Problems solved by technology

[0006] The main purpose of this application is to provide a brain age prediction method and device based on 3D convolutional neural network to solve the problem of insufficient prediction of children's brain age due to information loss in traditional machine learning models in related technologies. exact question

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  • Brain age prediction method and device based on 3D convolutional neural network
  • Brain age prediction method and device based on 3D convolutional neural network
  • Brain age prediction method and device based on 3D convolutional neural network

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[0030] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiment of the application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiment of the application. Obviously, the described embodiment is only It is an embodiment of a part of the application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0031] It should be noted that the terms "first" and "second" in the description and claims of the present application and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It should be understood that the data so used may be interchanged under appropriate circumstances for...

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Abstract

The invention discloses a brain age prediction method based on a 3D convolutional neural network. The method comprises the following steps: performing stratified sampling on brain nuclear magnetic resonance imaging data; inputting the brain nuclear magnetic resonance imaging data subjected to stratified sampling into a 3D convolutional neural network through multiple threads for training, and extracting feature data; constructing a brain age prediction regression model according to the extracted feature data; and outputting a brain age prediction result according to the brain age prediction regression model. According to the method and the device, the technical problem of inaccurate children brain age prediction caused by information loss in the aspect of feature selection of a traditionalmachine learning model in related technologies is solved, and the technical effect of improving the accuracy of children brain age prediction is achieved.

Description

technical field [0001] The present application relates to the field of deep learning technology, in particular, to a brain age prediction method and device based on a 3D convolutional neural network. Background technique [0002] Magnetic resonance imaging (MRI) provides an opportunity to evaluate brain development with its high spatial resolution and high density resolution, but it is difficult for children's brain development maturity to be evaluated empirically by radiologists and must be calculated based on computer quantitative measurements . Healthy human brain development is an extremely complex process in childhood, adolescence, and early adulthood, manifested in heterogeneity in the order and pattern of tissue development in different brain regions. In general, the white matter (WM) volume gradually increases with age during childhood and adolescence, while the gray matter (GM) volume decreases with age, and the development trends and rates of different brain regio...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/11G06T7/33G16B20/00G06N3/04G06N3/08
CPCG06T7/0012G06T7/11G06T7/33G16B20/00G06N3/08G06T2207/10088G06T2207/30016G06T2207/20081G06T2207/20084G06N3/045
Inventor 李秀丽曲太平卢光明俞益洲
Owner BEIJING SHENRUI BOLIAN TECH CO LTD
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