SPARKLING: Novel Non-Cartesian Sampling Schemes for Accelerated 2D Anatomical Imaging at 7T Using Compressed Sensing

Abstract : We present for the first time the implementation of novel non-Cartesian trajectories on a 7T scanner for 2D anatomical imaging. The proposed SPARKLING curves (Segmented Projection Algorithm for Random K-space sampLING) are a new type of non-Cartesian segmented sampling trajectories which allow fast and efficient coverage of the k-space according to a chosen variable density [1]. To demonstrate their potential, a high-resolution (0.4x0.4x3.0mm 3) T2*-weighted image was acquired with an 8-fold undersampled SPARKLING trajectory. Images were reconstructed using non-linear iterative reconstructions derived from the Compressed Sensing theory.
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Communication dans un congrès
25th annua meeting of the International Society for Magnetic Resonance Imaging, Apr 2017, Honolulu, United States. 2017
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https://hal.inria.fr/hal-01577200
Contributeur : Philippe Ciuciu <>
Soumis le : vendredi 25 août 2017 - 07:26:25
Dernière modification le : lundi 4 juin 2018 - 15:42:02

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  • HAL Id : hal-01577200, version 1

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Carole Lazarus, Pierre Weiss, Nicolas Chauffert, Franck Mauconduit, Michel Bottlaender, et al.. SPARKLING: Novel Non-Cartesian Sampling Schemes for Accelerated 2D Anatomical Imaging at 7T Using Compressed Sensing. 25th annua meeting of the International Society for Magnetic Resonance Imaging, Apr 2017, Honolulu, United States. 2017. 〈hal-01577200〉

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