DocumentCode
1766011
Title
Fast and Robust Design of Time-Optimal k-Space Trajectories in MRI
Author
Davids, Mathias ; Ruttorf, Michaela ; Zollner, Frank G. ; Schad, Lothar R.
Author_Institution
Comput. Assisted Clinical Med., Heidelberg Univ., Mannheim, Germany
Volume
34
Issue
2
fYear
2015
fDate
Feb. 2015
Firstpage
564
Lastpage
577
Abstract
Many applications in MRI such as accelerated receive and transmit sequences require the synthesis of nonuniform 3-D gradient trajectories. Several methods have been proposed to design these gradient trajectories in a time-optimal manner, subject to hardware specific gradient magnitude and slew rate constraints. In this work a novel method is derived that designs time-optimal trajectories, solely based on a set of arbitrarily chosen control points in k-space. In particular, no path constraint is required for the k-space trajectory. It is shown that the above problem can be formulated as a constrained optimization problem. The fact that the objective function is derived in an analytic manner allows for designing time-optimal 3-D gradient trajectories within only few seconds without any significant numerical instabilities. The utilization of the shape of the trajectory-serving as a degree of freedom-results in significantly accelerated trajectories compared to current standard methods. This is proven in an extensive evaluation of the proposed method and in comparison with what can be considered the current Gold Standard method. The proposed Gradient Basis Function method provides significant benefits over current standard methods in terms of the duration of the trajectory (in average 9.2% acceleration), computation time (acceleration by at least 25% up to factors of 100), and robustness (no significant numerical instabilities).
Keywords
biomedical MRI; gradient methods; optimisation; MRI; constrained optimization problem; gradient basis function method; magnetic resonance imaging; time-optimal 3D gradient trajectories; time-optimal k-space trajectories; Acceleration; Hardware; Linear programming; Optimization; Shape; Trajectory; Vectors; Control points; gradient hardware constraints; magnetic resonance imaging; sparse k-space trajectories; time-optimal gradient waveform design;
fLanguage
English
Journal_Title
Medical Imaging, IEEE Transactions on
Publisher
ieee
ISSN
0278-0062
Type
jour
DOI
10.1109/TMI.2014.2362681
Filename
6919289
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