Compressive sensing-based quick fine angular resolution diffusion imaging method
A technology with high angular resolution and imaging method, which is applied in the direction of using nuclear magnetic resonance image system for measurement, magnetic variable measurement, magnetic resonance measurement, etc., can solve the problem of low adaptability of diffusion-sensitive gradient magnetic field distribution method, low image acquisition quality, scanning Long time and other issues, to achieve the effect of reducing motion artifacts, shortening the acquisition process, and improving the reconstruction speed
Inactive Publication Date: 2013-04-17
PEKING UNIV
View PDF10 Cites 8 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
[0021] The technical problem to be solved by the present invention is to provide a fast and high-angular-resolution diffusion imaging method based on compressed sensing, which is used to solve the problems of low image acquisition quality, slow acquisition speed, long scanning time, and Low adaptability of diffusion-sensitive gradient magnetic field distribution method
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 moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0062] The principles and features of the present invention are described below in conjunction with the accompanying drawings, and the examples given are only used to explain the present invention, and are not intended to limit the scope of the present invention.
[0063] Such as figure 1 As shown, Embodiment 1 is a fast high angular resolution diffusion imaging method based on compressive sensing, and its implementation method is as follows.
[0064] 1. Step 1. Construct a unit sphere in the spherical coordinate system (radius r=1, azimuth angle phi∈[0,2π), elevation angle theta∈[0,π)), and distribute on the unit hemisphere according to the spiral distribution of the spherical surface Determine the distribution direction of the diffusion-sensitive gradient magnetic field, and flip half of the distribution directions of the diffusion-sensitive gradient magnetic field to the other hemisphere symmetrically with respect to the center of the sphere, so as to obtain all the distrib...
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
Login to view more Abstract
The invention relates to a compressive sensing-based quick fine angular resolution diffusion imaging method which comprises the following steps of: confirming the distribution directions of diffusion sensitive gradient magnetic fields according to a spherical helix distribution mode; setting an undersampled coding strategy for the distribution direction of each confirmed diffusion sensitive gradient magnetic field; acquiring a set of k space signals of the distribution direction of the first diffusion sensitive gradient magnetic field to be taken as reference images in the manner of full-sampling; inputting the distribution directions of the other diffusion sensitive gradient magnetic fields and the undersampled coding strategy of the distribution directions into a magnetic resonance scanner, and sequentially acquiring k space signals of the distribution directions; respectively subtracting each set of obtained k space signals with the k space signals of the reference image, rebuilding by a compressive sensing method to obtain difference value images, and overlapping the difference value images onto the reference images. According to the method, the small amount of k space signals can be acquired by the helix distribution method, the undersampled coding strategy and the HARDI data characteristics, so that an unknown image can be well rebuilt; and therefore, the sampling speed and the image rebuilding speed can be accelerated.
Description
technical field [0001] The invention relates to the technical field of magnetic resonance imaging, in particular to a fast and high-angular-resolution diffusion imaging method based on compression sensing. Background technique [0002] Below are some nomenclature explanations in this area, and its scope of use is limited to the present invention: [0003] K-space signal: In the process of magnetic resonance imaging, the original signal collected by the magnetic resonance spectrometer is different from the space where the image pixels are located, and is called k-space, so the corresponding original signal is called k-space signal. [0004] Phase encoding gradient magnetic field: In order to encode the spatial position, it is necessary to apply different magnetic field strengths at different positions, which requires the use of gradient magnetic fields. When the direction of the gradient points to the y direction of the space coordinate system, this direction is called the p...
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
Login to view more IPC IPC(8): G01R33/48
Inventor 高嵩王飞王浩宇
Owner PEKING UNIV
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
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