Brain age prediction method and system based on three-dimensional convolutional neural network

A three-dimensional convolution and neural network technology, applied in the field of image processing, can solve the problems of lack of end-to-end convenience, prediction accuracy cannot meet the needs of clinical applications, etc., and achieve the effect of high accuracy

Pending Publication Date: 2020-04-07
INST OF AUTOMATION CHINESE ACAD OF SCI
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Problems solved by technology

[0005] In the existing brain age prediction models based on structural images, most of them use traditional machine learning methods. These methods need to go through the process of feature extr

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  • Brain age prediction method and system based on three-dimensional convolutional neural network
  • Brain age prediction method and system based on three-dimensional convolutional neural network
  • Brain age prediction method and system based on three-dimensional convolutional neural network

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Embodiment Construction

[0067] Preferred embodiments of the present invention are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention, and are not intended to limit the protection scope of the present invention.

[0068] The purpose of the present invention is to provide a brain age prediction method based on a three-dimensional convolutional neural network, by preprocessing the historical structural magnetic resonance image data in the training sample set, by processing the image and the physiological age of the corresponding tester, The three-dimensional convolutional neural network is trained to obtain the trained three-dimensional convolutional neural network; through the trained three-dimensional convolutional neural network, the current structural magnetic resonance image data of the current tester can be identified, so that the brain age of the cu...

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Abstract

The invention relates to a brain age prediction method and system based on a three-dimensional convolutional neural network. The brain age prediction method comprises the steps: collecting a historical sample set which comprises a plurality of pairs of historical structure magnetic resonance image data and the physiological age of a corresponding tester, and dividing the historical sample set intoa training sample set and a testing sample set; preprocessing the historical structure magnetic resonance image data in the training sample set to obtain corresponding processed images; training thethree-dimensional convolutional neural network according to the processed images and the physiological ages of the corresponding testees to obtain a trained three-dimensional convolutional neural network; acquiring current structure magnetic resonance image data of a current tester; and based on the trained three-dimensional convolutional neural network, determining the brain age condition of thecurrent testee according to the current structure magnetic resonance image data, thus realizing end-to-end detection, and being high in the accuracy.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a brain age prediction method and system based on a three-dimensional convolutional neural network. Background technique [0002] The brain shows regular changes in structure and function during the process of development and aging. The pattern of this change is very complex, and it is impossible to obtain the results clinically with the naked eye. In practice, brain age is used as a measure of the pattern of change in this process. [0003] At present, the research on the development and aging trajectory of the brain is not very in-depth. We urgently need a high-precision brain age prediction model to fit the change trajectory of the brain during the development and aging process. On the one hand, it can help us understand the development and aging mechanism of the brain, and strengthen our understanding and understanding of the human brain; on the other hand, ...

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Application Information

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IPC IPC(8): G06T7/00G06N3/04G06N3/08A61B5/00A61B5/055
CPCG06T7/0012G06N3/084A61B5/4064A61B5/055G06T2207/10088G06T2207/20081G06T2207/20084G06T2207/30016G06N3/045
Inventor 饶光祥李昂刘冰刘勇
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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