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Abstract #2805

Real-time cardiac cine using supervised machine learning and compressed sensing with radial trajectory

Jingyuan Lyu1, Yu Ding1, Qi Liu1, and Jian Xu1

1UIH America., Houston, TX, United States

2D Real-time cardiac cine imaging is valuable for myocardiac function studies. Compared with Cartesian trajectory, Golden-angle (GA) radial acquisition is promising in patients with impaired breath-hold capacity [1]. The GA radial acquisition is an easy-to-implement and promising technique that features improved spatial-temporal resolution, and overcuts Cartesian sampling trajectories in reducing motion artifacts.

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