Minimizing echo and repetition times in magnetic resonance imaging using a double half‐echo k ‐space acquisition and low‐rank reconstruction

2020 ◽  
Author(s):  
Mark Bydder ◽  
Fadil Ali ◽  
Vahid Ghodrati ◽  
Peng Hu ◽  
Jingwen Yao ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Low Rank ◽  
Resonance Imaging ◽  
Space Acquisition

scholarly journals Influence of partial k-space filling on the quality of magnetic resonance images

2016 ◽  
Vol 49 (3) ◽  
pp. 158-164
Author(s):  
Tiago da Silva Jornada ◽  
Camila Hitomi Murata ◽  
Regina Bitelli Medeiros
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Magnetic Resonance Images ◽  
Resonance Imaging ◽  
Signal To Noise ◽  
T1 And T2 ◽  
Space Acquisition ◽  
Magnetic Resonance Imaging Equipment

Abstract Objective: To study the influence that the scan percentage tool used in partial k-space acquisition has on the quality of images obtained with magnetic resonance imaging equipment. Materials and Methods: A Philips 1.5 T magnetic resonance imaging scanner was used in order to obtain phantom images for quality control tests and images of the knee of an adult male. Results: There were no significant variations in the uniformity and signal-to-noise ratios with the phantom images. However, analysis of the high-contrast spatial resolution revealed significant degradation when scan percentages of 70% and 85% were used in the acquisition of T1- and T2-weighted images, respectively. There was significant degradation when a scan percentage of 25% was used in T1- and T2-weighted in vivo images (p ≤ 0.01 for both). Conclusion: The use of tools that limit the k-space is not recommended without knowledge of their effect on image quality.

scholarly journals Dynamic Magnetic Resonance Imaging Reconstruction Based on Nonconvex Low-Rank Model

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Lixia Chen ◽  
Bin Yang ◽  
Xuewen Wang
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Magnetic Resonance Images ◽  
Dynamic Magnetic Resonance Imaging ◽  
Low Rank ◽  
Data Sets ◽  
Resonance Imaging ◽  
Dynamic Magnetic Resonance ◽  
Imaging Reconstruction

The quality of dynamic magnetic resonance imaging reconstruction has heavy impact on clinical diagnosis. In this paper, we propose a new reconstructive algorithm based on the L+S model. In the algorithm, the l1 norm is substituted by the lp norm to approximate the l0 norm; thus the accuracy of the solution is improved. We apply an alternate iteration method to solve the resulting problem of the proposed method. Experiments on nine data sets show that the proposed algorithm can effectively reconstruct dynamic magnetic resonance images.

scholarly journals Line scan-based rapid magnetic resonance imaging of repetitive motion

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hankyeol Lee ◽  
Jeongtaek Lee ◽  
Jang-Yeon Park ◽  
Seung-Kyun Lee
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Time Course ◽  
Main Magnetic Field ◽  
Resonance Imaging ◽  
Repetitive Motion ◽  
Line Scan ◽  
Magnetic Resonance Imaging Mri ◽  
Motion Period ◽  
Space Acquisition

AbstractTwo-dimensional (2D) line scan-based dynamic magnetic resonance imaging (MRI) is examined as a means to capture the interior of objects under repetitive motion with high spatiotemporal resolutions. The method was demonstrated in a 9.4-T animal MRI scanner where line-by-line segmented k-space acquisition enabled recording movements of an agarose phantom and quail eggs in different conditions—raw and cooked. A custom MR-compatible actuator which utilized the Lorentz force on its wire loops in the scanner’s main magnetic field effectively induced the required periodic movements of the objects inside the magnet. The line-by-line k-space segmentation was achieved by acquiring a single k-space line for every frame in a motion period before acquisition of another line with a different phase-encode gradient in the succeeding motion period. The reconstructed time-course images accurately represented the objects’ displacements with temporal resolutions up to 5.5 ms. The proposed method can drastically increase the temporal resolution of MRI for imaging rapid periodic motion of objects while preserving adequate spatial resolution for internal details when their movements are driven by a reliable motion-inducing mechanism.

EXACT LOW-RANK MATRIX RECOVERY VIA NONCONVEX SCHATTEN p-MINIMIZATION

2013 ◽  
Vol 30 (03) ◽  
pp. 1340010 ◽  
Author(s):  
LINGCHEN KONG ◽  
NAIHUA XIU
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Low Rank ◽  
Magnetic Resonance Imaging System ◽  
Resonance Imaging ◽  
Matrix Recovery ◽  
Rank Matrix ◽  
Restricted Isometry Constant ◽  
Low Rank Matrix Recovery ◽  
Low Rank Matrix

The low-rank matrix recovery (LMR) arises in many fields such as signal and image processing, quantum state tomography, magnetic resonance imaging, system identification and control, and it is generally NP-hard. Recently, Majumdar and Ward [Majumdar, A and RK Ward (2011). An algorithm for sparse MRI reconstruction by Schatten p-norm minimization. Magnetic Resonance Imaging, 29, 408–417]. had successfully applied nonconvex Schatten p-minimization relaxation of LMR in magnetic resonance imaging. In this paper, our main aim is to establish RIP theoretical result for exact LMR via nonconvex Schatten p-minimization. Carefully speaking, letting [Formula: see text] be a linear transformation from ℝm×n into ℝs and r be the rank of recovered matrix X ∈ ℝm×n, and if [Formula: see text] satisfies the RIP condition [Formula: see text] for a given positive integer k ∈ {1, 2, …, m – r}, then r-rank matrix can be exactly recovered. In particular, we obtain a uniform bound on restricted isometry constant [Formula: see text] for any p ∈ (0, 1] for LMR via Schatten p-minimization.

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