Structural nuclear magnetic resonance image processing method used for Alzheimer disease early detection

A technology of Alzheimer's disease and nuclear magnetic resonance, applied in the field of biomedical signal processing, can solve the problems of undersampling, loss of structural information, high order of data, etc., and achieve the effect of improving accuracy

Inactive Publication Date: 2013-10-09
SHANDONG UNIV
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AI Technical Summary

Problems solved by technology

Since the number of samples is usually limited, the high order of the vectorized data may cause undersampling problems
Moreover, vectorization will also destroy the spatial structure of the original 3D data, resulting in the loss of a large amount of structural information

Method used

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  • Structural nuclear magnetic resonance image processing method used for Alzheimer disease early detection
  • Structural nuclear magnetic resonance image processing method used for Alzheimer disease early detection
  • Structural nuclear magnetic resonance image processing method used for Alzheimer disease early detection

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Embodiment Construction

[0016] The present invention selects Open Access Series of Imaging Studies (OASIS for short, http: / / www.oasis-brains.org ) database as experimental data, 216 individuals with complete information were selected from 416 individuals for the experiment, and were divided into 81 AD patients (CDR>0) and 135 normal people (CDR=0), among them, the normal people over 64 years old are elderly normal people, a total of 65 people. Since the incidence of AD increases significantly with age, the classification results of AD patients and elderly healthy people are specially made to illustrate the effectiveness of the method of the present invention. figure 2 It is the classification result of 81 AD patients and 135 normal people, image 3 It is the classification result of 81 AD patients and 65 elderly normal people.

[0017] The present invention processes AD sMRI data in the form of tensor, combines UMPCA and LS algorithms to perform feature extraction and feature selection on the pre...

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Abstract

The invention provides a structural nuclear magnetic resonance image processing method used for Alzheimer disease early detection. The method includes the steps of firstly, conducting feature extraction on a structural nuclear magnetic resonance image expressed in a tensor form through a non-correlation multi-linear algorithm, then, conducting selecting on an extracted algorithm through the Laplacian value algorithm, and finally sending the selected feature into an SVM classifier and conducting training, classifying/diagnosing. According to the method, feature extraction is conducted on the structural nuclear magnetic resonance image through a tensor analysis method, spatial structure information of original data is reserved, the step of feature selection is added, redundant information in the feature is further reduced, and the feature with higher discernment is selected. According to experimental data, the method has high classification accuracy, and a possible auxiliary tool is provided for early diagnosis of the Alzheimer disease.

Description

technical field [0001] The invention relates to a nuclear magnetic resonance image processing method for early detection of Alzheimer's disease, belonging to the technical field of biomedical signal processing. Background technique [0002] Alzheimer's disease (AD) is a common chronic neurodegenerative disease in the elderly. The accumulation of senile plaques and tangles of nerve fibers in the brain of AD patients leads to memory dysfunction and other cognitive function declines, eventually leading to death. In the actual clinical diagnosis, the diagnosis of AD is mainly based on a series of cognitive test evaluations after the corresponding symptoms of dementia appear, combined with imaging and other examination methods to make a diagnosis. Such diagnostic results are somewhat subjective, and when the patient has obvious clinical symptoms, the disease is already in the middle and late stages, and it is difficult for the existing treatment methods to achieve effective trea...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46G06K9/62A61B5/055
Inventor 刘琚赖春露吴强
Owner SHANDONG UNIV
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