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Abstract #3161

Accelerated T1 weighted PROPELLER imaging of the brain with deep-learning based parallel imaging reconstruction

Motohide Kawamura1, Daiki Tamada1, Kazuyuki Sato2, Masahiro Hamasaki2, Satoshi Funayama1, Tetsuya Wakayama3, Utaroh Motosugi4, Hiroyuki Morisaka1, and Hiroshi Onishi1
1Department of Radiology, University of Yamanashi, Chuo, Japan, 2Division of Radiology, University of Yamanashi Hospital, Chuo, Japan, 3MR Collaboration and Development, GE Healthcare, Hino, Japan, 4Department of Radiology, Kofu-Kyoritsu Hospital, Kofu, Japan


PROPELLER sequence is useful because of its robustness to patient motion. Longer acquisition than FSE is a major drawback limiting its wider application in clinical practice. Here, we propose an accelerated T1 weighted PROPELLER of the brain using deep learning based parallel imaging (PI) reconstruction. Our method can unfold highly undersampled aliased images (PI factor = 7), enabling 2.3 times faster acquisition than full-sampling. A preliminary reader study with prospectively undersampled data showed that the proposed method significantly outperformed a conventional SENSE reconstruction in terms of streak artifact.

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