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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