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MRI image reconstruction method based on enhanced sparse representation of image blocks

A sparse representation and image reconstruction technology, applied in image enhancement, image analysis, image data processing, etc., can solve the problems of long sampling time and large sampling data, and achieve the effect of enhancing sparsity, improving accuracy, and good visual effect

Active Publication Date: 2018-05-04
成都国一科技有限公司
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Problems solved by technology

Traditional MRI imaging needs to sample the original data K-space according to the Nyquist sampling theorem, and the sampling data is large, which will inevitably cause the problem of long sampling time

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  • MRI image reconstruction method based on enhanced sparse representation of image blocks
  • MRI image reconstruction method based on enhanced sparse representation of image blocks
  • MRI image reconstruction method based on enhanced sparse representation of image blocks

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Embodiment Construction

[0032] refer to figure 1 , the present invention is an MRI image reconstruction method based on enhanced sparse representation of image blocks, and the specific steps include the following:

[0033] Step 1, establish the ordering of image blocks and image reconstruction model.

[0034] (1a) Input a piece of MRI original K-space observation data y, and use the result of zero-filling and inverse Fourier transform on y as the initial reconstructed image x;

[0035] (1b) Use the image block extraction matrix to extract the target image block x in the reconstructed image x i , and build each target image block x i Its corresponding coefficient α i The ordering transformation model of :

[0036]

[0037] where Ψ represents the wavelet transform, Represents the matrix that sorts the pixels in the image block, θ i for the sort sequence, is the sequence of adjustment factors for the phase, R i Extract the matrix for the image block;

[0038] (1c) According to the target i...

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Abstract

The invention discloses an MRI image reconstruction method based on the enhanced sparse representation of image blocks, and belongs to the technical field of digital image processing. The method is used for improving the coefficient sparseness and the estimation performance by utilizing the pixel sequencing and the non-convex norm constraint in image blocks. According to the method, firstly, a target image block is extracted from an MRI image, and then a sequencing training model based on image blocks is built. Meanwhile, a reconstruction model of the MRI image is built according to the coefficient non-convex constraint. After that, an alternate direction method is adopted to iteratively solve a sequencing matrix and a sparse coefficient in the model. Based on the estimated sparse coefficient, a final MRI image is reconstructed. According to the method, through sequencing pixels in the image blocks, the performance of the sparse transformation is improved. Meanwhile, the non-convex norm minimization constraint is carried out on coefficients, so that estimated coefficients are closer to real coefficients. Based on the method of the invention, the overall effect of reconstructed images is better and the detail information is richer. Meanwhile, the reconstitution accuracy is higher. Therefore, the method can be used for reconstructing MRI images.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, and particularly relates to a method for enhancing the sparsity of transform domain coefficients by sorting pixels in an image block and reconstructing images by using non-convex norms to constrain coefficients, which is used for high-quality medical images recover. Background technique [0002] Magnetic resonance imaging (MRI) technology is an imaging technology that uses the principle that atomic nuclei with magnetic moments can produce transitions between energy levels under the action of a magnetic field. This technology has become an important detection method in clinical medicine because of its advantages of no biological damage and high imaging resolution. However, there is a very important deficiency in MRI, that is, the imaging time is too slow, causing the patient to remain still for a long time, and the movement of the patient during the period will also cause imaging...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06K9/46
CPCG06T2207/10088G06T2207/20064G06T2207/30016G06T2207/30168G06V10/40G06V10/50G06V10/513G06T5/90
Inventor 刘书君曹建鑫沈晓东唐明春张新征王品
Owner 成都国一科技有限公司
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