Compressed sensing magnetic resonance fast imaging method

Abstract

The invention relates to a compressed sensing magnetic resonance fast imaging method, which comprises the following steps of: adopting a quadruple sampling module to sample a K space to obtain a K space undersampled signal y; obtaining a Fourier undersampled signal of a wavelet subband through the signal y, wherein the Fourier undersampled signal of the wavelet subband comprises a low-frequency subband Fourier undersampled signal uLL and a high-frequency subband Fourier undersampled signal un; rebuilding the low-frequency subband Fourier undersampled signal uLL to obtain a low-frequency subband to build a mathematic model, and rebuilding the high-frequency subband Fourier undersampled signal un to obtain a high-frequency subband N, which belongs to an element of a set (HL,LH,HH), according to the mathematic model; and carrying out wavelet inverse transformation on the low-frequency subband and the high-frequency subband N which belongs to the element of the set (HL,LH,HH) so as to obtain a rebuilt image. According to the compressed sensing magnetic resonance fast imaging method, the signal sparsity is improved through dictionary learning, and through utilizing a relationship between the wavelet subband and the K space, the traditional problem of image rebuilding in compressed sensing magnetic resonance is optimized to be a problem which has a smaller computing scale and can be solved through parallel computing, so that a final image can be rebuilt quickly.

Description

technical field [0001] The invention relates to a magnetic resonance fast imaging method, in particular to a compressed sensing magnetic resonance fast imaging method. Background technique [0002] Magnetic Resonance Imaging (MRI, Magnetic Resonance Imaging) is to obtain the image information of human tissue through magnetic field, and display the molecular environment of the intrinsic tissue nucleus with pixels, which provides a more accurate clinical diagnostic tool for medical observation. It is a comprehensive technology integrating physics, superconducting technology, strong magnetism, large signal transmission and radiation, weak signal reception and processing, digital signal processing, computer real-time control, image reconstruction and many other technologies. [0003] Compressed sensing theory has been successfully applied to magnetic resonance imaging. Compressed sensing theory uses the sparsity of the signal under a certain basis to realize a high-quality reco...

AI Technical Summary

Problems solved by technology

[0006] According to the traditional compressed sensing MRI theory, although the reconstruction of MRI images can be realized, the sparsity of the signal is not fully utilized, the number of samples is large, and the MRI scanning time is long.

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