Non-convex low-rank reconstruction method for rapid magnetic resonance (MR) imaging

A magnetic resonance, non-convex technology, applied in the field of medical imaging, to achieve multiple image details, reduce reconstruction artifacts, and reduce algorithm complexity

Active Publication Date: 2015-09-23
南昌市云影医疗科技有限公司
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Problems solved by technology

The defect of the existing technology is to solve the low-rank matrix recovery

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  • Non-convex low-rank reconstruction method for rapid magnetic resonance (MR) imaging
  • Non-convex low-rank reconstruction method for rapid magnetic resonance (MR) imaging
  • Non-convex low-rank reconstruction method for rapid magnetic resonance (MR) imaging

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[0056] In order to make the purpose, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the accompanying drawings and examples of implementation. The specific embodiments described here are only used to explain the technical solution of the present invention, and are not limited to the present invention.

[0057] The invention will be described in more detail hereinafter with reference to the accompanying drawings which illustrate the invention. Now refer to the attached figure 1 A non-convex low-rank reconstruction algorithm for magnetic resonance fast imaging according to the present invention is described. According to the method of the present invention, the technical scheme of the present invention is based on the non-local similarity and low-rank characteristics of MR image blocks, establishes a low-sampling-rate MRI reconstruction model based on image low-rank priors...

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Abstract

The invention relates to a non-convex low-rank reconstruction method for rapid MR imaging. An MR image data reconstruction mathematic model based on low-rank prior information of non-local similar image blocks is established, and iterative solution is carried out on the model in a direction alternative iteration method; a non-convex p norm of the low-rank matrix of the non-local image model with the low-rank prior information is solved by deposition and iteration of Taylor first-order approximation and the singular value, a similar image block is obtained, and a reconstruction image is solved via iteration by increasing the auxiliary variable and separating the variable. The image prior information is used to combine the non-local similarity with the low-rank characteristic of the image block, the Fourier transform and the characteristic of the low-rank matrix are used to simplify the calculation process, the complexity of algorithm is reduced, the performance of the reconstructed MRI images by part of K space data is improved, the image can be reconstructed more accurately with less scanning and measurement, pseudo shadows of the images are reduced, and rapid MRI is realized.

Description

technical field [0001] The invention belongs to the field of medical imaging, in particular to magnetic resonance imaging. Background technique [0002] Magnetic resonance imaging (MRI) technology is a medical diagnostic technology that can obtain detailed diagnostic images of living organs and tissues. It has the advantages of no damage and no radiation, and has been widely used in medical clinical and scientific research fields. Magnetic resonance imaging technology can provide doctors with clearer and higher-contrast medical images of human body structure. It was welcomed by clinicians when it was born, and it was quickly applied clinically and became an indispensable inspection method for some disease diagnoses. However, MRI has the disadvantage of slow imaging speed. In order to reduce the imaging time of MRI, there are currently two ways: one is to improve the hardware equipment, such as multi-coil parallel imaging, fast imaging gradient sequence design, etc.; the othe...

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Application Information

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IPC IPC(8): G06T5/00
Inventor 卢红阳刘且根吴新峰龙承志王玉皞
Owner 南昌市云影医疗科技有限公司
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