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Abstract #2666

Distribution-controlled and optimally spread non-Cartesian sampling curves for accelerated in vivo brain imaging at 7 Tesla

Carole Lazarus1, Pierre Weiss2, Loubna El Gueddari1, Franck Mauconduit3, Alexandre Vignaud4, and Philippe Ciuciu1

1CEA/NeuroSpin - INRIA/Parietal, Gif-sur-Yvette, France, 2CNRS - ITAV, Toulouse, France, 3Siemens Healthineers, Saint-Denis, France, 4CEA/NeuroSpin/UNIRS/METRIC, Gif-sur-Yvette, France

This work reports the use of new non-Cartesian k-space trajectories whose improved efficiency allows to significantly reduce MR scan time with minimum deterioration of image quality. Instead of using simple geometrical patterns, we introduce an approach inspired from stippling techniques, which automatically designs optimized sampling patterns along any distribution by taking full advantage of the hardware capabilities. Our strategy leads to drastically accelerated acquisitions, as demonstrated by our experimental results at 7T on in vivo human brains. We compare our method to widely-used non-Cartesian trajectories (spiral,radial) and demonstrate its superiority regarding image quality and robustness to system imperfections.

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