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Compressed sensing magnetic resonance fast imaging method

An imaging method and compressed sensing technology, applied in the fields of sensors, medical science, diagnostic recording/measurement, etc., can solve the problems of insufficient use of signal sparsity, long magnetic resonance scanning time, and large quantity

Inactive Publication Date: 2013-06-12
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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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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Embodiment Construction

[0036] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0037] see figure 1 , figure 1 The flow chart of the steps of the compressive sensing magnetic resonance fast imaging method provided by the embodiment of the present invention includes the following steps:

[0038] Step S1: Using a quadruple sampling module to sample the K-space to obtain the under-sampled signal y of the K-space.

[0039] see figure 2 and image 3 , figure 2 The schematic diagram of the steps of the quadruple sampling module provided by the embodiment of the present invention, image 3 The step flowchart of the quadruple sampling module provided by the embodiment...

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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...

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Application Information

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IPC IPC(8): A61B5/055
Inventor 梁栋刘建博王圣如刘新郑海荣
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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