Three-regular magnetic resonance image reconstruction method based on Split Bregman iteration

A magnetic resonance image, iterative technology, applied in image data processing, 2D image generation, instruments, etc., can solve the problem of high computational complexity, difficult to effectively eliminate aliasing artifacts and Gibbs ringing, and limited image reconstruction accuracy And other issues

Inactive Publication Date: 2016-06-15
HARBIN UNIV OF SCI & TECH
View PDF4 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the magnetic resonance map reconstruction method in the prior art is mainly realized by single or double regularization terms, which has high computational complexity and is difficult to effectively eliminate aliasing artifacts and Gibbs ringing. The problem of limited image reconstruction accuracy

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Three-regular magnetic resonance image reconstruction method based on Split Bregman iteration
  • Three-regular magnetic resonance image reconstruction method based on Split Bregman iteration
  • Three-regular magnetic resonance image reconstruction method based on Split Bregman iteration

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0050] Illustrate the specific embodiment of the present invention in conjunction with accompanying drawing, a kind of three regular magnetic resonance image reconstruction method based on SplitBregman iteration of the present invention, comprises the following steps:

[0051] Step 1, obtaining under-sampled k-space data by measurement;

[0052] The undersampled k-space initial data f 0 Obtained by the following formula:

[0053] f 0 =RFu+N;

[0054] initial reconstructed image u 0 for: u 0 =F -1 f 0 ;

[0055] In the formula, R is a measurement matrix, and R in this embodiment is a radial measurement matrix with a sampling rate of 0.2 (that is, an acceleration factor of 5).

[0056] F is the Fourier transform, u is the original image, and N is the complex Gaussian noise.

[0057] Step 2. Use the full variation, short support wavelet and wavelet with high regularization order and high vanishing moment to constrain the regularization term, and obtain the reconstructed ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

A three-regular magnetic resonance image reconstruction method based on Split Bregman iteration relates to a magnetic resonance image reconstruction method. The invention aims to solve the problems that magnetic resonance image reconstruction methods in the prior art are high in computation complexity, cannot eliminate aliasing artifacts and Gibbs ringing, and have limited image reconstruction precision. The method comprises the following steps: k space data without being sampled are obtained through measurement; regularization term constraint is conducted by using a total variation, short support wavelet and a high order, high vanishing moment wavelet, and a reconstructed image is obtained after Split Bregman iteration; the reconstructed image obtained in the second step is subjected to error determination, and if the error does not satisfy a preset condition, the second step is repeated until the preset condition is satisfied, and the reconstructed image is obtained. The method improves the quality of the reconstructed image while ensuring quick reconstruction.

Description

technical field [0001] The invention relates to a magnetic resonance image reconstruction method, in particular to a three-regular magnetic resonance image reconstruction method based on SplitBregman iteration, and belongs to the technical field of medical magnetic resonance imaging. Background technique [0002] Magnetic Resonance Imaging (MRI) is a method based on the spin characteristics of biological atomic nuclei, using radio frequency pulses to excite objects in a static magnetic field to generate magnetic resonance signals, and at the same time to encode frequency and phase space (K space) information, using Fu Lie transform is a technique for obtaining digital images. It is widely used in medical imaging due to its advantages of no damage, multiple image types and high image contrast in the process of examining patients, but its further development is limited due to its long data acquisition time. How to improve the real-time performance of magnetic resonance imagin...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06T11/00
CPCG06T11/003
Inventor 宋立新张建广王乾
Owner HARBIN UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap