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Feature brain region positioning method of magnetic resonance imaging data based on deep learning

A magnetic resonance imaging and deep learning technology, applied in the medical field, can solve the problems of data waste and easy to be affected by the subjective factors of clinicians, and achieve high accuracy

Pending Publication Date: 2021-03-09
WEST CHINA HOSPITAL SICHUAN UNIV
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Problems solved by technology

The recognition of medical images is a branch of image recognition. Compared with other digital images, medical images contain a lot of information that reflects the health level of the human body. However, at present, this part of information is still mainly analyzed manually, which is not only susceptible to subjective factors of clinicians. impact, but also easily lead to waste of data

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  • Feature brain region positioning method of magnetic resonance imaging data based on deep learning
  • Feature brain region positioning method of magnetic resonance imaging data based on deep learning
  • Feature brain region positioning method of magnetic resonance imaging data based on deep learning

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Embodiment Construction

[0055] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0056] The method for locating characteristic brain regions based on deep learning magnetic resonance imaging data disclosed by the present invention is actually processed as follows:

[0057] Before the MRI data is analyzed, the MRI data is preprocessed. The main purpose of the MRI preprocessing is to detect and repair the differences in the acquisition process of the subject data.

[0058] The preprocessing process is as figure 1 As shown, the specific steps of MRI data preprocessing are:

[0059]1. Eliminate the first 10 time-point data of each subject’s MRI data: When collecting MRI data, the initial MRI signal may not be stable and other factors. Therefore, considering the uniformity of the magnetic field, it is necessary to eliminate the first 10 time-point...

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Abstract

The invention discloses a feature brain region positioning method of magnetic resonance imaging data based on deep learning, which comprises the following steps of: a, preprocessing original MRI imagedata to obtain preprocessed MRI data; b, performing ALFF mapping extraction on the preprocessed MRI data to obtain image data after mapping extraction; c, taking the image after mapping extraction asan input quantity of a convolutional neural network model, performing deep learning, with the convolutional neural network model being of an Inception structure, and obtaining a classification resultof MRI image data; and d, determining feature brain region positioning according to the classification result. The feature brain region positioning can be obtained through the resting-state MRI imageby adopting a related algorithm in deep learning, and the accuracy is high.

Description

technical field [0001] The invention relates to the field of medical technology, in particular to a method for locating characteristic brain regions based on deep learning magnetic resonance imaging data. Background technique [0002] In recent years, various neurological diseases continue to emerge, which not only seriously affect the health and quality of life of patients, but also bring huge economic burdens to patients' families and society. Resting state functional magnetic resonance imaging is a method widely used in basic research and clinical research of various neurological diseases. It mainly measures intrinsic or spontaneous brain activity based on low-frequency fluctuations of blood oxygen level-dependent signals. Magnetic resonance imaging has great potential in the identification of characteristic information of neurological diseases. The traditional approach to impact data analysis is to perform hypothesis testing on voxels in the brain individually and can o...

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Application Information

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IPC IPC(8): G06T7/73G06K9/62G06N3/04G06N3/08
CPCG06T7/73G06N3/08G06T2207/10088G06T2207/30016G06N3/045G06F18/241
Inventor 龚启勇张俊然杨豪李国豪
Owner WEST CHINA HOSPITAL SICHUAN UNIV
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