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A Classification Method for MRI Images of Alzheimer's Disease

A classification method and image technology, applied in image analysis, image enhancement, image data processing and other directions, can solve the problems of low classification accuracy and difficult feature extraction of classification methods, and achieve the effect of good classification results.

Active Publication Date: 2020-07-28
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] Aiming at the above-mentioned deficiencies in the prior art, a kind of Alzheimer's disease MRI image classification method provided by the present invention solves the problems of difficulty in feature extraction and low classification accuracy of existing classification methods

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  • A Classification Method for MRI Images of Alzheimer's Disease
  • A Classification Method for MRI Images of Alzheimer's Disease
  • A Classification Method for MRI Images of Alzheimer's Disease

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Embodiment Construction

[0030] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.

[0031] Such as figure 1 Shown, a kind of classification method of Alzheimer's disease MRI image, comprises the following steps:

[0032] S1. Collect enough MRI (magnetic resonance imaging) images of AD (Alzheimer's disease), MCI (mild cognitive impairment) and NC (normal) populations.

[0033] S2. Preprocess the MRI image to obtain slices in multiple 2D forms in the three directions of Axial (axial), Sagittal (radial), and...

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Abstract

The invention discloses a classification method of MRI images of Alzheimer's disease. Invented using the idea of ​​metric learning to construct a loss function and use it to train a set of convolutional neural networks. On the one hand, for each 3D data, multiple 2D form slices are obtained in the three directions of Axial, Sagittal, and coronal, and input into a set of convolutional neural networks at the same time, which not only retains 3D data information to a certain extent, but also avoids It solves the problem that it is difficult to find a suitable data set for pre-training using 3D convolutional neural network and the problem of serious over-fitting; sex. Finally, better classification results can be obtained.

Description

technical field [0001] The invention relates to the technical field of image classification, in particular to an MRI image classification method for Alzheimer's disease. Background technique [0002] As a development direction of image processing and machine learning, medical image processing is one of the fields most closely related to human life. With the development of population aging, Alzheimer's disease, as one of the most common senile dementias, has brought a great impact on people's lives, especially the lives of patients and their families. As an important branch of the field of medical image classification, the classification of Alzheimer's Disease (AD) is of great significance to the computer-aided diagnosis of AD, especially for the early diagnosis of the disease and the timely control of the deterioration of the disease. [0003] The image data used in the present invention is an MRI (Magnetic Resonance Imaging) image. MRI images can provide a wealth of morph...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06K9/62
CPCG06T7/0012G06T2207/30016G06T2207/10088G06T2207/20081G06F18/24
Inventor 程建周娇苏炎洲郭桦林莉
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA