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Dynamic magnetic resonance image reconstruction method based on improved robust tensor principal component analysis

A principal component analysis and magnetic resonance image technology, applied in image enhancement, image analysis, image data processing, etc., can solve problems such as ignoring correlation and redundancy, affecting the quality of dynamic images, etc., to reduce interference and improve reconstruction Image efficiency, the effect of reducing the amount of sampled data

Inactive Publication Date: 2019-12-03
ZHEJIANG SCI-TECH UNIV
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Problems solved by technology

Clearly, reshaping a high-order tensor (3D image) into a sequence of (2D) matrices or vectors ignores the correlations and redundancies inherent in the space of the 3D data, thus affecting the quality of the reconstructed dynamic image

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  • Dynamic magnetic resonance image reconstruction method based on improved robust tensor principal component analysis
  • Dynamic magnetic resonance image reconstruction method based on improved robust tensor principal component analysis
  • Dynamic magnetic resonance image reconstruction method based on improved robust tensor principal component analysis

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Embodiment Construction

[0036] In order to describe the present invention more specifically, the technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0037] like figure 1 As shown, the dynamic MRI image reconstruction method based on improved robust tensor principal component analysis, the specific steps are as follows:

[0038] 1. Place the radial sampling plate according to figure 2 (a), figure 2 (b), figure 2 (c) and figure 2 The high-dimensional radial sampling trajectory mode shown in (d) samples the K-space data of the dynamic nuclear magnetic resonance image to obtain undersampled data, and the undersampled data is represented by tensor γ; the high-dimensional radial sampling trajectory mode is specifically: First, the radial sampling plate is placed on the first frame of the dynamic MRI image, and then the radial sampling plate is rotated by an angle k( i-1), the value of i is 2,3,...,N 3 , the frame number o...

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Abstract

The invention discloses a dynamic magnetic resonance image reconstruction method based on improved robust tensor principal component analysis. Precision and speed of an existing dynamic magnetic resonance image reconstruction method need to be improved. The method comprises: using tensors for representing K space data obtained through radial sampling, using a tensor robust principal component analysis tool for constructing an image reconstruction model, and guaranteeing the space integrity of high-dimensional data; providing a new tensor nuclear norm to constrain a low-rank part, so that the overall low-rank constraint is improved while the low-rank processing efficiency is ensured; carrying out time-frequency transformation on the sparse part and then carrying out threshold processing toimprove the reconstruction precision; finally, using an iterative soft threshold shrinkage algorithm to solve the optimization problem of the algorithm, and the image reconstruction quality and the accelerated reconstruction efficiency can be effectively improved. According to the invention, a high-quality diagnosis part image can be reconstructed in a short time, and a clear image can still be obtained at an extremely low sampling rate.

Description

technical field [0001] The invention belongs to the technical field of magnetic resonance medical imaging, and in particular relates to a dynamic magnetic resonance image reconstruction method based on improved robust tensor principal component analysis. Background technique [0002] Dynamic Magnetic Resonance Imaging (dMRI) technology can provide information on dynamic changes in human tissue that are not easily found in general MRI, so it has important clinical applications in medicine. However, its further application is restricted due to slow data acquisition and imaging speed. At present, Compressed Sensing (CompressedSensing) has been successfully applied to dMRI reconstruction, which reduces the number of data acquisitions and reduces the waiting time for patients to scan. In CS-dMRI, image reconstruction is an ill-posed problem, so improving image quality and reconstruction speed has always been a research hotspot in the field of magnetic resonance. [0003] In mos...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T11/00G06T7/168G06T7/136G06F17/16
CPCG06F17/16G06T7/136G06T7/168G06T11/005G06T2207/10088G06T2207/20056
Inventor 蒋明峰沈倩男李杨郑俊褒
Owner ZHEJIANG SCI-TECH UNIV
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