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Magnetic resonance diffusion tensor denoising method and system

A technology of diffusion tensor and magnetic resonance, applied in diagnostic recording/measurement, image data processing, medical science, etc., can solve problems affecting the image quality of diffusion parameters, achieve the effect of suppressing noise and improving estimation accuracy

Active Publication Date: 2017-06-16
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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Problems solved by technology

This method is widely used, but the systematic error in the image denoising process may be further transmitted to the subsequent tensor calculation, which will affect the quality of various diffusion parameter images

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  • Magnetic resonance diffusion tensor denoising method and system
  • Magnetic resonance diffusion tensor denoising method and system
  • Magnetic resonance diffusion tensor denoising method and system

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Embodiment Construction

[0031] The present invention is based on the magnetic resonance diffusion weighted imaging technology, utilizes the inherent characteristics (such as sparsity) of the diffusion tensor model and the relative anisotropy of the diffusion, and based on the theoretical framework of maximum a posteriori probability estimation, directly acquires denoising from the collected K-space data The final diffusion tensor is used to realize magnetic resonance diffusion tensor imaging. The MRI diffusion tensor imaging mentioned here is a new method different from the diffusion weighted imaging, which can be used to describe the brain structure. For example, if an MRI tracks hydrogen atoms in water molecules, then diffusion tensor imaging maps the direction in which water molecules move, and a diffusion tensor image (presented differently than previous images) can reveal brain tumors How to affect nerve cell connections, guiding medical personnel to perform brain surgery. It can also reveal su...

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Abstract

The present invention provides a magnetic resonance diffusion tensor denoising method and system. The method is based on the magnetic resonance diffusion weighted imaging model and the Gaussian distribution property of the sampling noise, utilizes the sparseness of the relative anisotropy of the diffusion, and adopts the maximum a posteriori probability estimation The method of K-space directly obtains the denoised diffusion tensor matrix corresponding to each spatial position. The invention can avoid the influence of the image denoising error on the estimation of the diffusion tensor, suppress the noise in the diffusion tensor more effectively, and improve the estimation precision of the diffusion tensor.

Description

technical field [0001] The present invention relates to magnetic resonance imaging technology, in particular to a magnetic resonance diffusion tensor denoising method and system. Background technique [0002] Diffusion Tensor Imaging (DTI) is a new imaging method developed on the basis of Diffusion Weighted Imaging (DWI). It uses the diffusion anisotropy of water molecules for imaging, and can non-destructively evaluate tissue from the microscopic field. The integrity of the structure provides more information for the prevention, diagnosis and treatment of diseases. However, DTI requires longer scan times and has a lower signal-to-noise ratio than other MRI techniques. [0003] In order to improve the signal-to-noise ratio of diffusion tensor imaging, the more direct method is to take the average through multiple sampling and reduce the K-space sampling area. These methods have certain applications in practice, but will increase the scanning time and affect the spatial res...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00A61B5/055
Inventor 彭玺梁栋刘新郑海荣
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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