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Verfasst von:Davids, Mathias [VerfasserIn]   i
 Ruttorf, Michaela [VerfasserIn]   i
 Zöllner, Frank G. [VerfasserIn]   i
 Schad, Lothar R. [VerfasserIn]   i
Titel:Fast and robust design of time-optimal k-space trajectories in MRI
Verf.angabe:Mathias Davids, Michaela Ruttorf, Member, IEEE, Frank G. Zöllner, Member, IEEE, and Lothar R. Schad
Jahr:2015
Jahr des Originals:2014
Umfang:14 S.
Fussnoten:Gesehen am 20.11.2018 ; Date of publication October 09, 2014
Titel Quelle:Enthalten in: Institute of Electrical and Electronics EngineersIEEE transactions on medical imaging
Ort Quelle:New York, NY : Institute of Electrical and Electronics Engineers, 1982
Jahr Quelle:2015
Band/Heft Quelle:34(2015), 2, Seite 564-577
ISSN Quelle:1558-254X
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).
DOI:doi:10.1109/TMI.2014.2362681
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext ; Verlag: http://dx.doi.org/10.1109/TMI.2014.2362681
 Volltext: https://ieeexplore.ieee.org/document/6919289
 DOI: https://doi.org/10.1109/TMI.2014.2362681
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:MRI
 Acceleration
 Algorithms
 biomedical MRI
 constrained optimization problem
 Control points
 gradient basis function method
 gradient hardware constraints
 gradient methods
 Hardware
 Imaging, Three-Dimensional
 Linear programming
 magnetic resonance imaging
 Magnetic Resonance Imaging
 optimisation
 Optimization
 Shape
 sparse k-space trajectories
 time-optimal 3D gradient trajectories
 time-optimal gradient waveform design
 time-optimal k-space trajectories
 Trajectory
 Vectors
K10plus-PPN:1583893636
Verknüpfungen:→ Zeitschrift

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