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Nuclear magnetic resonance image reconstruction method based on sparse representation and non-local similarity

A kind of nuclear magnetic resonance image, non-local similarity technology, applied in the field of image processing, can solve the problem of difficult reconstruction of image details, poor image reconstruction effect, etc.

Inactive Publication Date: 2014-09-24
HANGZHOU DIANZI UNIV
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Problems solved by technology

Existing methods use total variation constraints and sparse domain l 1 The convex optimization reconstruction method with norm constraints is not effective for image reconstruction with complex texture structure, and the details of the image are difficult to reconstruct

Method used

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  • Nuclear magnetic resonance image reconstruction method based on sparse representation and non-local similarity
  • Nuclear magnetic resonance image reconstruction method based on sparse representation and non-local similarity
  • Nuclear magnetic resonance image reconstruction method based on sparse representation and non-local similarity

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Embodiment Construction

[0041] The present invention is described in detail below in conjunction with embodiment:

[0042] Step (1) obtains the initial reference image for reconstruction, specifically:

[0043] Fourier transform is performed on the NMR grayscale image with a size of 256×256, and the Fourier transform coefficients are sampled by random downsampling with variable density, that is, the part of the Fourier coefficient corresponding to the low-frequency information of the image is more Sampling, less sampling of the part of the Fourier coefficient corresponding to the high-frequency information of the image; the amount of data obtained by sampling can account for 16%-30% of the total Fourier transform data, such as 20%; for the obtained sampled data matrix The missing part is filled with zero values, and then the initial reference image x for reconstruction is obtained by two-dimensional inverse Fourier transform (0) ;

[0044] Step (2) blocks the reference image and classifies the imag...

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Abstract

The invention relates to a nuclear magnetic resonance image reconstruction method based on sparse representation and non-local similarity, and mainly aims to improve the reconstruction quality of a nuclear magnetic resonance image. The method comprises the following specific steps: firstly, sampling a Fourier transform coefficient corresponding to the nuclear magnetic resonance image by adopting a variable-density random down-sampling method, and performing Fourier inversion on sampled data to obtain an initial reference image for reconstructing; secondly, blocking the reference image to obtain similar structural characteristics of each type of image sub-blocks and obtain corresponding dictionaries of each type of image sub-blocks and sparse representation coefficients of the image sub-blocks; lastly, estimating the original image by using the non-local similarity of the image sub-blocks, restraining the sparse coefficients of the image sub-blocks, combining the sparsity of the image in a wavelet domain, and performing iterative reconstruction through a hybrid regular term solving model. By adopting the method, the non-local similarity of the image is fully utilized, complex textures in the image can be effectively reconstructed, and the quality of a reconstructed quality is improved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a nuclear magnetic resonance image reconstruction method, in particular to a nuclear magnetic resonance image reconstruction method based on sparse representation and non-local similarity. Background technique [0002] Magnetic resonance imaging is an important medical imaging technique that is widely used in clinic. Research in recent years has shown that compressed sensing theory can reconstruct images better using less sampled data than other methods. This theory points out that in the problem of reconstructing magnetic resonance images, if the image can be represented sparsely in a certain transformation domain, then the original image can be completely reconstructed with a high probability by using the downsampled data in the frequency domain corresponding to the nuclear magnetic resonance image. One approach to image reconstruction is to transform the image reconstr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T11/00G06T5/00
Inventor 陈华华杜文琦
Owner HANGZHOU DIANZI UNIV
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