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Abstract #1835

Density optimization of low-discrepancy k-space trajectories for accelerated 2D single-point imaging

Pia Gebhard1, Tobias Speidel1, Fabian Bschorr1, Julian Schüle1, and Volker Rasche1
1Ulm University Medical Center, Ulm, Germany

Synopsis

Keywords: Data Acquisition, Simulation/Validation

Motivation: Single-point imaging (SPI) is highly effective for imaging short T2(*) relaxation times and regions of susceptibility, but suffers from long acquisition times.

Goal(s): SPI methods inherently allow for versatile sampling and are therefore well suited for integration with reconstruction-based image acceleration methods.

Approach: We present a 2D realization of a previously introduced 3D quasi-random sampling scheme with enhanced PSF optimization algorithm for coherent artifact behavior reduction.

Results: The method was validated through simulations and phantom studies, showing promising results for faster and more efficient imaging.

Impact: The clinical application of pure phase encoding methods as SPI and CSI is limited by the related long acquisition times. The presented optimized trajectories enable high undersampling and related reduction of scan time for broader clinical applications.

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