Method for quickly reconstructing magnetic resonance images on basis of adaptive structure low-rank matrixes

A magnetic resonance image and low-rank matrix technology, which is applied in the field of alternating iterative magnetic resonance image reconstruction based on an adaptive structure low-rank matrix regularization model, can solve the problems of image detail loss and slow magnetic resonance imaging speed

Inactive Publication Date: 2018-05-04
HARBIN INST OF TECH
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[0004] The purpose of the present invention is to propose a fast magnetic resonance image reconstruction method based on an adaptive str

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  • Method for quickly reconstructing magnetic resonance images on basis of adaptive structure low-rank matrixes
  • Method for quickly reconstructing magnetic resonance images on basis of adaptive structure low-rank matrixes
  • Method for quickly reconstructing magnetic resonance images on basis of adaptive structure low-rank matrixes

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[0049] The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0050] Such as figure 1 Shown, the specific implementation steps of the present invention are as follows:

[0051] (1) Utilize the pre-set undersampling template to obtain part of the k-space data, in order to verify the effect of the present invention, a group of simulated images and a group of reference magnetic resonance images are adopted, such as figure 2 As shown, they are block-smoothed image (a) and forward brain magnetic resonance image (b). Fourier transform is performed on the reference image to collect the original k-space data. The acquired under-sampled k-space data is expressed as Among them, A is the operation operator for undersampling in k-space after performing Fourier transform on the magnetic resonance image, n is the additive noise that may exist in actual sampling, b is the obtained k-space undersampling data, is the image ...

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Abstract

The invention discloses a method for quickly reconstructing magnetic resonance images on the basis of adaptive structure low-rank matrixes, and relates to the technical field of magnetic resonance imaging. The quality of reconstructed images can be improved by the aid of the method. The method includes steps of (1), acquiring partial k spatial data; (2), solving partial derivatives and constructing Toeplitz matrixes; (3), building image reconstruction models; (4), deforming the Toeplitz matrixes and decomposing characteristic values; (5), computing weight coefficient matrixes and leading the weight coefficient matrixes into the reconstruction models; (6), introducing auxiliary variables and Lagrange multipliers and carrying out iterative solution by the aid of ADMM (alternating direction method of multipliers) algorithms; (7), judging whether convergence conditions are met by reconstruction results or not; (8), acquiring ultimate magnetic resonance images when iterative times are reached, or updating the Toeplitz matrixes by the current reconstructed images obtained by means of iteration, and returning the step (4) to continue operation. Compared with first-order and second-order structure low-rank and total-variation methods, the method has the advantage that the reconstructed images with high quality can be obtained by the aid of the method under the condition of identical under-sampling multiples.

Description

technical field [0001] The invention relates to the technical field of magnetic resonance imaging, in particular to an alternate iterative magnetic resonance image reconstruction method based on an adaptive structure low-rank matrix regularization model under the compressed sensing theory. Background of the invention [0002] Magnetic resonance imaging technology has been widely used in clinical medical diagnosis due to its significant advantages such as no ionizing radiation, multi-parameter control, and high imaging quality. However, the slow imaging speed is currently the main bottleneck limiting the development of MRI. Longer scanning time will easily lead to involuntary physiological movement of the scanned person, resulting in image artifacts, lowering the imaging quality, and failing to meet the requirements of high-precision detection and positioning and high-resolution imaging such as brain functional imaging and cardiac dynamic imaging. Scanning can also be uncomf...

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IPC IPC(8): G01R33/48G01R33/56G01R33/561
CPCG01R33/4818G01R33/5608G01R33/561
Inventor 胡悦刘小晗赵旷世
Owner HARBIN INST OF TECH
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