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Multi-tensor-based magnetic resonance diffusion weighted image structure adaptive smoothing method

A diffusion-weighted image and magnetic resonance technology, applied in the field of medical image processing, can solve the problems of low accuracy of fiber structure information and poor noise suppression, and achieve the effects of smooth avoidance, improved accuracy, and image noise suppression.

Active Publication Date: 2015-05-13
严格集团股份有限公司
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Problems solved by technology

[0017] The present invention is to solve the problem of poor noise suppression in the existing method, thus making the obtained fiber structure information of each voxel low in accuracy, and provides an adaptive smoothing method for magnetic resonance diffusion weighted image structure based on multiple tensors

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  • Multi-tensor-based magnetic resonance diffusion weighted image structure adaptive smoothing method
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  • Multi-tensor-based magnetic resonance diffusion weighted image structure adaptive smoothing method

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specific Embodiment approach 1

[0039] Specific implementation mode one: see Figure 14 Describe this embodiment, the multi-tensor based magnetic resonance diffusion weighted image structure adaptive smoothing method described in this embodiment, the steps to realize the method are as follows:

[0040] Step 1: Select parameter λ, parameter a and total number of iterations k N The value of , set the initial neighborhood radius h (0) , set the current number of iterations k=1, calculate h (1) =ah (0) , the value range of λ is 0.5~5, the value range of a is 1N The range of value is 5~10, h (0) The value range of is 0.5~1.5;

[0041] Step 2: Calculate the initial fiber structure information of each voxel p and set parameters in Indicates that the direction of existence of the voxel is fibers, the proportion of which is Indicates how many different running directions exist for the fibers in this voxel, the parameter The value range of is 1~2;

[0042] Step 3: For each voxel p, record q as h cente...

specific Embodiment approach 2

[0044] Specific embodiment 2: This embodiment is a further limitation of specific embodiment 1. In the second step, the initial fiber structure information of each voxel p is calculated. is calculated using the constrained compressive sensing method.

[0045] The initial fiber structure information of each voxel p described in this embodiment Not only constrained compressive sensing methods can be used, but other methods can also be used.

specific Embodiment approach 3

[0046] Specific embodiment 3: This embodiment is a further limitation of specific embodiment 1. In the step 3, the weight of all voxels within the neighborhood radius to the voxel is calculated according to the fiber structure information of each voxel p , so as to perform weighted smoothing on the MRI diffusion weighted image, and the method of recalculating the fiber structure information of each voxel after smoothing is:

[0047] calculate Where ρ(p,q) is the Euclidean distance from voxel p to voxel q;

[0048] calculate which function Indicates the difference in fiber structure information between voxel p and voxel q;

[0049] calculate weight where the kernel function K loc ( ) and K st ( ) are two monotonically decreasing functions with a domain of [0,∞), and satisfy K loc (0)=K st (0)=1, when x≥1 K loc (x)=K st (x) = 0;

[0050] Calculate the sum of the weights of all voxels in the neighborhood U(p) to p

[0051] calculate S ...

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Abstract

The invention discloses a multi-tensor-based magnetic resonance diffusion weighted image structure adaptive smoothing method, relates to a magnetic resonance diffusion weighted image smoothing method, belongs to the field of medical image processing, and solves the problem that the accuracy of the fiber structure information of each obtained voxel is low because of poor noise suppression in the conventional method. The multi-tensor-based magnetic resonance diffusion weighted image structure adaptive smoothing method comprises the following steps: firstly, selecting related parameters, and setting an initial neighborhood radius; secondly, calculating the initial fiber structure information of each voxel; thirdly, calculating the weights of all voxels in the neighborhood radius on the voxel according to the fiber structure information, performing weighted smoothing on a magnetic resonance diffusion weighted image, and recalculating the fiber structure information of each voxel after the magnetic resonance diffusion weighted image is smoothed; fourthly, judging whether a stopping criterion for iteration is met or not, if not, expanding the neighborhood radius and continuing to performing the third step, or else, ending the calculating. The multi-tensor-based magnetic resonance diffusion weighted image structure adaptive smoothing method is applicable to processing the information of the magnetic resonance diffusion weighted image.

Description

technical field [0001] The invention relates to a magnetic resonance diffusion weighted image smoothing method, which belongs to the field of medical image processing. Background technique [0002] Magnetic resonance diffusion imaging is currently the only non-invasive method that can measure the diffusion motion and imaging of water molecules in tissues in vivo. It detects the microstructure of tissues by measuring and quantifying the diffusion information of water molecules in tissues. The diffusion information of water molecules along different directions is included in a set of diffusion weighted images (Diffusion Weighted Image, DWI) with different diffusion weighted gradient directions, and the fiber bundle structure information in each voxel can be analyzed by modeling the diffusion function ( mainly the running direction of the fibers). According to the running direction of fiber bundles in each voxel, the three-dimensional structure of tissue fiber bundles can be r...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 刘宛予楚春雨朱跃敏马格宁.伊莎贝尔
Owner 严格集团股份有限公司
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