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Magnetic resonance image reconstruction method based on conjugate gradient method of nonlinear function

A conjugate gradient method and magnetic resonance image technology, applied in the field of image processing, can solve problems such as slow speed and lack of practicability

Active Publication Date: 2019-10-22
NANJING MEDICAL UNIV
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Problems solved by technology

The conjugate gradient method is a classic and simpler algorithm for solving this problem, but its disadvantage is that it is too slow, so it lacks practicability in real applications

Method used

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  • Magnetic resonance image reconstruction method based on conjugate gradient method of nonlinear function
  • Magnetic resonance image reconstruction method based on conjugate gradient method of nonlinear function
  • Magnetic resonance image reconstruction method based on conjugate gradient method of nonlinear function

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Embodiment

[0089] Select brain, cerebrovascular and knee tomographic MR images for experiments, the resolution of the images is 512×512 pixels, and use the mean square error (MSE), peak signal-to-noise ratio (PSNR) and structured similarity (SSIM) to evaluate the images Refactor quality.

[0090] figure 1 The original MR images from the hospital are the three parts of the brain, cerebrovascular and knee.

[0091] Fig. 2-4 has shown under the sampling rate of 30%, adopts the conjugate gradient method (being called for short A conjugate gradient method) based on the non-linear action function proposed by the present invention and the conjugate gradient method (abbreviating B for short) in conjunction with backtracking line search The MR images reconstructed by the conjugate gradient method are the MR images of the brain, cerebrovascular, and knee in sequence. The method proposed by the present invention has good restoration effect on MR images of different human body parts.

[0092] Fig...

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Abstract

The invention relates to a conjugate gradient method based on a non-linear action function, in particular to a magnetic resonance image reconstruction method based on the conjugate gradient method ofthe non-linear action function, which comprises the following steps of: 1, acquiring undersampled k-space magnetic resonance image data; 2, converting L0 norm optimization into solving of an L1 norm optimization problem; 3, considering the noise in the imaging process; 4, utilizing k-space data consistency; 5, introducing a nonlinear action function Sigmoid function to dynamically adjust the steplength of the conjugate gradient method; and 6, utilizing the conjugate gradient method modified in the step 5. According to the method, the step length of the conjugate gradient method can be dynamically adjusted without line search, and the convergence speed is greatly increased under the condition of ensuring the precision of the reconstructed image. According to the method, the convergence rate of the conjugate gradient method can be greatly improved while the image reconstruction precision is ensured, and the method is suitable for under-sampling magnetic resonance image reconstruction ofdifferent human body parts.

Description

technical field [0001] The invention relates to a conjugate gradient method for dynamically adjusting step size based on a nonlinear action function, in particular to a magnetic resonance image reconstruction method based on the conjugate gradient method of a nonlinear action function, and belongs to the field of image processing. Background technique [0002] The sampling mode of k-space in traditional MRI satisfies the Nyquist criterion, and violation of the Nyquist criterion will lead to artifacts in the linear reconstruction of images. The redundancy of MRI data makes domestic and foreign scholars devote themselves to finding ways to reduce the amount of data without reducing the quality of imaging. The theory of compressed sensing breaks through the Nyquist criterion, and the compressibility of MR images in a specific transform domain makes it naturally suitable for the theory of compressed sensing. [0003] Accurately reconstructing images is an important step in the ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T11/00G06T5/00G06F17/16
CPCG06T11/003G06F17/16G06T2207/10088G06T2207/30168G06T5/70
Inventor 王伟高子涵胡晓雯其他发明人请求不公开姓名
Owner NANJING MEDICAL UNIV
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