Title
Smoothed random-like trajectory for compressed sensing MRI.
Abstract
In this paper, we explores a rapid imaging method based on a proposed random-like trajectory for compressed sensing (CS) which requires the sampling trajectory should satisfy the Restricted Isometry Property (RIP) condition. In the existing CS literature, the attentions are on randomly sampling points on the conventional trajectories. However, the proposed trajectory is a random-like trajectory generated based on the High Order Chirp (HOC) sequences, which use the Traveling Salesman Problem (TSP) solver to choose a "short" trajectory and design a time optimal gradient waveforms to satisfy the gradient amplitude and slew rate limitation. The MR physical feasibility of the proposed method is verified by the Bloch simulation, and the simulations show that the proposed method can reduce artifacts than conventional Spiral trajectory under the CS framework.
Year
DOI
Venue
2012
10.1109/EMBC.2012.6345953
EMBC
Keywords
Field
DocType
rapid imaging method,hoc sequence,spiral trajectory,traveling salesman problem,travelling salesman problems,bloch simulation,high order chirp,biomedical mri,sampling trajectory,compressed sensing mri,rip condition,smoothed random like trajectory,tsp solver,restricted isometry property
Computer vision,Computer science,Travelling salesman problem,Chirp,Sampling (statistics),Artificial intelligence,Solver,Slew rate,Trajectory,Compressed sensing,Restricted isometry property
Conference
Volume
Issue
ISSN
2012
null
1557-170X
ISBN
Citations 
PageRank 
978-1-4577-1787-1
2
0.39
References 
Authors
2
5
Name
Order
Citations
PageRank
Haifeng Wang1215.87
Xiaoyan Wang2208.83
Yihang Zhou3113.04
Yuchou Chang419415.86
Yong Wang520.39