Magnetic resonance interventional imaging method and system based on low rank and sparse decomposition, and medium

A technology of sparse decomposition and imaging method, which is applied in the direction of using nuclear magnetic resonance image system for measurement, magnetic resonance measurement, and measurement of magnetic variables, etc., which can solve the problems of difficult real-time imaging and interventional navigation, difficult real-time imaging navigation, etc., to avoid motion Artifacts, good reconstructed image quality, effects of high downsampling rates

Active Publication Date: 2021-06-01
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

However, due to the limitation of imaging time, conventional MRI methods are difficult to achieve real-time imaging and interventional navigation
Although the current magnetic resonance dynamic imaging for heartbeat and

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  • Magnetic resonance interventional imaging method and system based on low rank and sparse decomposition, and medium
  • Magnetic resonance interventional imaging method and system based on low rank and sparse decomposition, and medium
  • Magnetic resonance interventional imaging method and system based on low rank and sparse decomposition, and medium

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Embodiment

[0068] A magnetic resonance interventional imaging method based on low-rank and sparse decomposition provided by the present invention comprises the following steps:

[0069] Step 1: During the intervention, the k-space data is collected continuously using the golden angle radial sampling method;

[0070] In order to achieve fast MRI interventional imaging, the golden angle radial sampling method is adopted to continuously collect k-space data during the intervention process, that is, the sampling radial spoke interval angle is the "golden angle", such as figure 1 (a) shown.

[0071] Step 2: Group the collected spatial data;

[0072] In dynamic magnetic resonance imaging, in the prior art, all k-space data are usually collected retrospectively and reconstructed, and each frame of image needs to be reconstructed with a certain number of radial spokes, such as figure 1 (b) shown. This kind of retrospective reconstruction is not suitable for MRI interventional imaging that req...

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Abstract

The invention provides a magnetic resonance interventional imaging method and system based on low rank and sparse decomposition, and a medium, and the method comprises the steps of: 1, continuously collecting k space data in a golden angle radial sampling mode in an interventional process; 2, grouping the collected k space data; and 3, reconstructing a magnetic resonance intervention image by adopting a method based on low-rank and sparse decomposition and framelet transformation. According to the method, based on grouped k space collection and reconstruction, reconstruction can be carried out under the condition that little data is acquired, the time resolution is high, and the real-time performance is good.

Description

technical field [0001] The present invention relates to the technical field of magnetic resonance interventional imaging, in particular, to a method, system and medium of magnetic resonance interventional imaging based on low-rank and sparse decomposition; in particular, to a method for k-space using golden angle radial sampling, based on An Interventional Magnetic Resonance Imaging Method for Image Reconstruction with Low-Rank and Sparse Decomposition. Background technique [0002] Interventional MRI (i-MRI) is an important method for magnetic resonance image-guided therapy. Magnetic resonance images provide better soft tissue contrast than other imaging modalities such as CT and ultrasound. This could greatly improve the outcomes of procedures such as biopsies and deep brain stimulation (DBS). However, due to the limitation of imaging time, conventional MRI methods are difficult to achieve real-time imaging and interventional navigation. Although the current magnetic re...

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Application Information

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IPC IPC(8): G01R33/48
CPCG01R33/4818
Inventor 冯原何钊朱亚南邱苏豪张小群
Owner SHANGHAI JIAO TONG UNIV
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