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A parallel magnetic resonance imaging reconstruction method combining total variation Lp pseudo norms based on self-consistency of feature vectors

A technology that combines total variation and magnetic resonance imaging, and is used in 2D image generation, image enhancement, image data processing, etc.

Active Publication Date: 2019-06-21
KUNMING UNIV OF SCI & TECH
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Problems solved by technology

However, due to the influence of factors such as dynamic corrosion, chemical shift and small field of view (Field of view, FOV), the L-containing 1 Some small overlapping artifacts appear in the reconstructed image of the ESPIRiT reconstruction method of the regularization term

Method used

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  • A parallel magnetic resonance imaging reconstruction method combining total variation Lp pseudo norms based on self-consistency of feature vectors
  • A parallel magnetic resonance imaging reconstruction method combining total variation Lp pseudo norms based on self-consistency of feature vectors
  • A parallel magnetic resonance imaging reconstruction method combining total variation Lp pseudo norms based on self-consistency of feature vectors

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Embodiment 1

[0053] Embodiment 1: as Figure 1-2 As shown, in the ESPIRiT model, the sensitivity information operator s at each spatial point r of the image r It can usually be obtained by solving the following problem:

[0054]

[0055] In the formula, is the convolution of positive semidefinite matrix values ​​for each position r in the image space, s r yes The eigenvalue of is the eigenvector of "1", and r represents the k-space position index variable. is defined as:

[0056]

[0057] in, Is a two-dimensional (twodimensional, 2D) Fourier transform matrix for vectorized multi-coil images, F m and F n are m-point and n-point Fourier transform matrices respectively, I C is the identity matrix of C×C, N=m×n represents the number of pixels of the 2D image, and also represents the total number of all k-space positions, m and n are the number of rows and columns of a single coil 2D image, C Indicates the total number of coil images, Represents the Kronecker product. in ...

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Abstract

The invention relates to a self-consistent parallel magnetic resonance imaging reconstruction method combining total variation Lp pseudo norms based on feature vectors, and belongs to the technical field of medical magnetic resonance imaging. The invention provides an ESPIRiT parallel imaging reconstruction algorithm containing a joint total variation Lp pseudo norm regularization term based on aniteration self-consistency parallel imaging reconstruction ESPIRiT framework of a feature vector. The method comprises the following steps: firstly, decomposing a reconstruction problem into a gradient calculation problem and a denoising problem containing sparse regular terms by adopting an OS technology; secondly, denoising is carried out by applying an MM algorithm; and finally, FISTA is usedfor acceleration. Experimental results show that compared with a traditional reconstruction algorithm using L1 regular terms, the proposed new algorithm using LpJTV regular terms based on the ESPIRiTreconstruction model can more effectively improve the reconstruction quality of the image.

Description

technical field [0001] The invention relates to a parallel magnetic resonance imaging reconstruction method based on the self-consistency of eigenvectors and the joint full variation Lp pseudo-norm, and belongs to the technical field of magnetic resonance imaging. Background technique [0002] Magnetic Resonance Imaging (MRI) is a non-invasive and non-ionizing imaging technique for visualization of body structures that provides excellent contrast in different soft tissues than most other imaging modalities. However, MRI is usually slow due to data sampling time constraints. The proposal of parallel imaging technology can effectively reduce the scanning time and accelerate the magnetic resonance imaging. At present, there are mainly two parallel imaging methods: (1) If the sensitivity information is known, each coil can accurately estimate the sensitivity profile, and reconstruct the image through the estimated sensitivity information. Such as: Sensitivity Encoding (SENSiti...

Claims

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Application Information

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IPC IPC(8): G06T11/00G06T5/00
Inventor 段继忠鲍中文
Owner KUNMING UNIV OF SCI & TECH
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