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Abstract #4521

Extracting a cine cardiac cycle without respiratory motion from real-time free-breathing images with unsupervised motion correction

Haris Saybasili 1 , Marie-Pierre Jolie 2 , and Bruce Spottiswoode 1

1 Siemens Healthcare, Chicago, Illinois, United States, 2 Imaging and Computer Vision, Siemens Corporation, Corporate Technology, NJ, United States

Real-time free-breathing imaging methods are viable alternatives to conventional segmented cine imaging for patients that cannot hold their breath. However, heart-rate changes during real-time acquisitions result in a different number of phases per beat/slice. Methods of obtaining a predefined number of cardiac phases per beat/slice from real-time images has been shown previously. However, cardiac phases acquired during inconsistent respiratory phases are hard to analyze due to respiratory motion. In this work, we propose an unsupervised motion correction scheme to generate high SNR, single heart-beat breath-held (end expiration) cine images from any real-time free-breathing acquisition covering multiple heart-beats.

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