Abstract #2981

Accelerated Compressed Sensing 3D multi-parametric imaging Toward Isotropic1mm3 Imaging

Naoyuki Takei¹, Akifumi Hagiwara^2,3, Shohei Fujita², Masaaki Hori², Ken-Pin Hwang⁴, Marcel Warntjes⁵, Suchandrima Banerjee⁶, Florian Wiesinger⁷, Shigeki Aoki⁸, and Hiroyuki Kabasawa¹

¹MR Applications and Workflow, GE Healthcare, Tokyo, Japan, ²Radiology, Juntendo University School of Medicine, Tokyo, Japan, ³Radiology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan, ⁴Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States, ⁵SyntheticMR, Linkoping, Sweden, ⁶MR Applications and Workflow, GE Healthcare, Menlo Park, CA, United States, ⁷ASL Europe, GE Healthcare, Munich, Germany, ⁸Juntendo University School of Medicine, Tokyo, Japan

A multi-parametric technique, 3D QALAS, accelerated using compressed sensing, was implemented to yield images of the brain at high spatial resolution of 1mm isotropic with multiple contrast weightings as well as parametric maps from a single scan. Compressed sensing factor of 1.5 combined with parallel imaging was used to accelerate scan time. The proposed 3D technique is expected to achieve both stable image quality and tissue segmentation accuracy with short imaging time.

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