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Abstract #3445

Synergistic Combination of Golden-angle Radial Sampling and Dual-Subspace Modeling for Rapid and Robust High Spatiotemporal Resolution MRA

Zhifeng Chen1,2 and Lirong Yan1,2
1USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States, 2Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States

Synopsis

This study proposes a rapid and robust ASL-based time-resolved MRA technique with high spatiotemporal resolution termed Dual-Subspace MRA (DS-MRA), which employs subspace modeling from both temporal and control/label dimensions as sparsity constraints to improve the robustness of image reconstruction with under-sampled golden-angle radial dynamic MRA. The performance of DS-MRA was compared with conventional iGRASP and 5-dimensional GRASP. Our preliminary data suggests that DS-MRA outperforms conventional GRASP reconstructions with less residual streaking artifacts and noise, especially at higher acceleration rates.

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Keywords