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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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https://hal.inria.fr/hal-01577200
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Submitted on : Friday, August 25, 2017 - 7:26:25 AM
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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. ⟨hal-01577200⟩

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