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Abstract #0021

Super-Resolution Multi-band ASL using Slice Dithered Enhanced Resolution (SLIDER) Technique

Qinyang Shou1, Xingfeng Shao1, and Danny Wang1
1University of Southern California, Los Angeles, CA, United States

Arterial Spin Labelling (ASL) is a noninvasive imaging technique that can quantitatively measure Cerebral Blood Flow (CBF). However, existing ASL techniques generally have a low spatial resolution due to a relative low Signal-to-noise ratio (SNR). In this study, we develop a super-resolution ASL method by combining the Slice Dithered Enhanced Resolution (SLIDER) with multi-band ASL with optimized slice-dependent background suppression to enhance both the resolution and SNR. The reconstructed images achieve a resolution of isotropic 2x2x2 mm3, and show increased spatial and temporal SNR compared to standard high-resolution ASL images.

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