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High-quality reconstruction method for parallel magnetic resonance imaging with joint total variation based on self-consistency

A combined total variation and magnetic resonance imaging technology, applied in image enhancement, image data processing, instruments, etc., can solve problems such as difficult coil sensitivity and achieve the effect of SNR improvement

Active Publication Date: 2017-12-05
SOUTHWEST PETROLEUM UNIV
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Problems solved by technology

However, it is often very difficult to accurately estimate the sensitivity of the coil

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  • High-quality reconstruction method for parallel magnetic resonance imaging with joint total variation based on self-consistency
  • High-quality reconstruction method for parallel magnetic resonance imaging with joint total variation based on self-consistency
  • High-quality reconstruction method for parallel magnetic resonance imaging with joint total variation based on self-consistency

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Embodiment Construction

[0060] Further describe the technical scheme of the present invention in detail below in conjunction with accompanying drawing:

[0061] The present invention is an efficient reconstruction method proposed based on the SPITiT framework.

[0062] SPIRiT is a parallel imaging reconstruction method based on self-calibration, which interpolates the missing frequency points during subsampling coil by coil, and then merges the multi-coil images into one image. In SPIRiT, an interpolation kernel g ij It is obtained by calibrating the data fully sampled in the center of the frequency domain (usually called a self-calibration signal). if x i represents the entire frequency-domain data of the i-th coil, then the calibration-based consistency criterion can be written as:

[0063]

[0064] In the formula, N c Indicates the number of coils, "*" indicates the convolution operation. Convolution kernel g ij Known as the SPIRiT core.

[0065] The consistency criterion for all coils c...

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Abstract

The invention discloses a self-consistency-based high-quality reconstruction method for parallel magnetic resonance imaging with joint total variation. The invention is based on the SPIRiT framework and aims at the reconstruction problem of parallel imaging containing JTV and JL1 compound regularization terms. A high-quality reconstruction algorithm. First, transform the constrained reconstruction problem into an unconstrained optimization problem, then simplify the data fidelity item and self-correction item, and then use the operator splitting technique to transform the simplified reconstruction problem into a gradient calculation problem And a denoising problem containing JTV and JL1 compound regularization terms, the denoising problem of compound regularization terms is solved by a newly designed algorithm based on Split Bregman technology. Finally, it is accelerated by FISTA. The invention designs experiments to compare the reconstruction performance of the new algorithm and other commonly used algorithms. Experimental simulations show that the convergence speed of the new algorithm is equivalent to that of the POCS algorithm, and the SNR of the reconstructed image is greatly improved.

Description

technical field [0001] The invention relates to a high-quality reconstruction method of parallel magnetic resonance imaging based on self-consistency and including joint full variation. Background technique [0002] Magnetic resonance imaging (Magnetic Resonance Imaging, MRI) can provide good human soft tissue contrast, and has no radiation, so it has gradually become an indispensable imaging tool in modern clinical medicine. However, limited by physical and physiological factors, the acquisition speed of MRI signals is very slow. Parallel imaging is a common technique to increase acquisition speed. The introduction of SMASH and SENSE marks that parallel imaging has become a feasible technology. Parallel imaging uses multiple coils with different sensitivities to the magnetic resonance signal to simultaneously acquire magnetic resonance signals. The use of sensitivity information reduces the number of data used for reconstruction, thereby increasing the speed of acquisiti...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
Inventor 段继忠罗仁泽苏赋邓魁郑勉汪敏曹玉英
Owner SOUTHWEST PETROLEUM UNIV
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