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High-order Tensor Feature Parameters Extraction Method for Diffusion Kurtosis Tensor Imaging

A technology of characteristic parameters and extraction methods, which is applied in the field of medical devices and can solve problems such as lack of uniform standards

Active Publication Date: 2015-12-02
TIANJIN UNIV
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Problems solved by technology

At present, there are many researches on the diagnosis of Alzheimer's disease, and some research progress has been made, but there is still a lack of uniform standards. Scholars at home and abroad have also actively adopted various methods for research

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  • High-order Tensor Feature Parameters Extraction Method for Diffusion Kurtosis Tensor Imaging

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Embodiment Construction

[0069] The present invention aims to propose a new and practical method for extracting magnetic resonance imaging parameters of human brain white matter structural abnormalities. The variance tensor and kurtosis tensor of the diffusion displacement distribution are obtained by fitting the DWI signals detected in multiple directions. The feature extraction method analyzes the anisotropy of the tissue to achieve the purpose of objectively evaluating the degree of lesions.

[0070] The invention proposes a parameter image extraction method reflecting tissue structure characteristics based on the magnetic resonance diffusion kurtosis tensor imaging (MR-DKI, MR-diffusion kurtosis tensor imaging) theory. The technical process is as follows: the subject collects the diffusion-weighted signals of the tissue along multiple directions on the magnetic resonance scanner, and fits the second-order and fourth-order tensors that reflect the characteristics of the probability density function ...

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Abstract

The invention relates to the technical field of medical instruments, provides a novel practical method for extracting MRI (magnetic resonance imaging) parameters of structural abnormality of white matters of a human brain, and aims to achieve the purpose of objectively evaluate the lesion degree by analyzing anisotropy of tissues through a certain characteristic extraction method. The invention adopts the technical scheme that the method for extracting high-order tensor characteristic parameters of diffusion kurtosis tensor imaging comprises the following steps: a subject collects diffusion weighted signals of tissues along a plurality of directions on a magnetic resonance scanner, then a second-order or fourth-order tensor that reflects diffusion and distribution probability density function of water molecules in the tissues can be obtained through fitting, and lesion characteristics of diffusion and distribution abnormality of the water molecules, caused by structural abnormality of the tissues, can be obtained through certain tensor analysis, wherein parameters from two different angles, including diffusion coefficient and kurtosis coefficient, are mainly included. The invention is mainly applied to design and manufacture of medical instruments.

Description

technical field [0001] The invention relates to the technical field of medical devices, in particular to a method for extracting high-order tensor characteristic parameters of diffusion kurtosis tensor imaging. Background technique [0002] Alzheimer's disease (AD) is the most common and important type of dementia, and it is also one of the three major diseases that seriously affect the health of the elderly. With the intensification of the aging degree of our country and even the global society, the economic burden and social burden brought by such diseases to the society will also be greatly increased. There is still no cure or other methods for this kind of disease, and the disease also has a long onset period and is hidden. Early diagnosis is of great significance for the early treatment of the disease. At present, there are many researches on the diagnosis of Alzheimer's disease, and some research progress has been made, but there is still a lack of uniform standards. ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/055
Inventor 赵欣陈元园倪红艳丁皓张希明东
Owner TIANJIN UNIV
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