Web: http://arxiv.org/abs/2209.09678

Sept. 21, 2022, 1:13 a.m. | Amin Ranem, John Kalkhof, Caner Özer, Anirban Mukhopadhyay, Ilkay Oksuz

cs.CV updates on arXiv.org arxiv.org

While machine learning approaches perform well on their training domain, they
generally tend to fail in a real-world application. In cardiovascular magnetic
resonance imaging (CMR), respiratory motion represents a major challenge in
terms of acquisition quality and therefore subsequent analysis and final
diagnosis. We present a workflow which predicts a severity score for
respiratory motion in CMR for the CMRxMotion challenge 2022. This is an
important tool for technicians to immediately provide feedback on the CMR
quality during acquisition, as …

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